Journal of Mechanical Engineering 2012 11 by Darko Svetak

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58 (2012) 11

Since 1955

Papers

623 633 642 653 665 673 683

Samo Venko, Boris Vidrih, Erik Pavlovič, Sašo Medved: Enhanced Heat Transfer on Thermo Active Cooling Wall Jiang Ding, Yangzhi Chen, Yueling Lv: Design of Space-Curve Meshing-Wheels with Unequal Tine Radii Ranko Božičković, Milan Radošević, Ilija Ćosić, Mirko Soković, Aleksandar Rikalović: Integration of Simulation and Lean Tools in Effective Production Systems – Case Study Robert Iacob, Diana Popescu, Peter Mitrouchev: Assembly/Disassembly Analysis and Modeling Techniques: A Review Baoping Cai, Yonghong Liu, Congkun Ren, Aibaibu Abulimiti, Xiaojie Tian, Yanzhen Zhang: Probabilistic Thermal and Electromagnetic Analyses of Subsea Solenoid Valves for Subsea Blowout Preventers Dražen Bajić, Luka Celent, Sonja Jozić: Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control Oğuz Çolak: Investigation on Machining Performance of Inconel 718 under High Pressure Cooling Conditions

Journal of Mechanical Engineering - Strojniški vestnik

Contents

11 year 2012 volume 58 no.

Strojniški vestnik Journal of Mechanical Engineering

Technical Editor Pika Škraba University of Ljubljana Faculty of Mechanical Engineering, Slovenia Editorial Office University of Ljubljana (UL) Faculty of Mechanical Engineering SV-JME Aškerčeva 6, SI-1000 Ljubljana, Slovenia Phone: 386-(0)1-4771 137 Fax: 386-(0)1-2518 567 E-mail: info@sv-jme.eu, http://www.sv-jme.eu

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Founders and Publishers University of Ljubljana (UL) Faculty of Mechanical Engineering, Slovenia University of Maribor (UM) Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia

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58 (2012) 11

Chamber of Commerce and Industry of Slovenia Metal Processing Industry Association

Since 1955

Strojniški vestnik Journal of Mechanical Engineering

Vidrih, Erik Pavlovič, Sašo Medved: nsfer on Thermo Active Cooling Wall Chen, Yueling Lv: rve Meshing-Wheels with Unequal Tine Radii Milan Radošević, Ilija Ćosić, Mirko Soković, ć: lation and Lean Tools in Effective Production Systems –

chining Performance of Inconel 718 under High Pressure

Journal of Mechanical Engineering - Strojniški vestnik

Popescu, Peter Mitrouchev: mbly Analysis and Modeling Techniques: A Review ong Liu, Congkun Ren, Aibaibu Abulimiti, Xiaojie Tian,

mal and Electromagnetic Analyses of Subsea Solenoid Valves Preventers Celent, Sonja Jozić: uence of Cutting Parameters on the Surface Roughness, ng Force in Face Milling in Off-Line Process Control

no. 11 2012 volume 58

Cover: Photography shows assembling of experimental setup in thermostatic chamber for experimental investigation of natural and mixed convection on cooled or heated vertical room wall. Aiding or opposing mixed convection is generated by air jet entering room through supply air diffuser mounted above the thermally activated wall. Image Courtesy: Hidria IMP Klima d.o.o. Slovenia, photo: Tine Mažgon.

year

International Editorial Board Koshi Adachi, Graduate School of Engineering,Tohoku University, Japan Bikramjit Basu, Indian Institute of Technology, Kanpur, India Anton Bergant, Litostroj Power, Slovenia Franci Čuš, UM, Faculty of Mech. Engineering, Slovenia Narendra B. Dahotre, University of Tennessee, Knoxville, USA Matija Fajdiga, UL, Faculty of Mech. Engineering, Slovenia Imre Felde, Bay Zoltan Inst. for Mater. Sci. and Techn., Hungary Jože Flašker, UM, Faculty of Mech. Engineering, Slovenia Bernard Franković, Faculty of Engineering Rijeka, Croatia Janez Grum, UL, Faculty of Mech. Engineering, Slovenia Imre Horvath, Delft University of Technology, Netherlands Julius Kaplunov, Brunel University, West London, UK Milan Kljajin, J.J. Strossmayer University of Osijek, Croatia Janez Kopač, UL, Faculty of Mech. Engineering, Slovenia Franc Kosel, UL, Faculty of Mech. Engineering, Slovenia Thomas Lübben, University of Bremen, Germany Janez Možina, UL, Faculty of Mech. Engineering, Slovenia Miroslav Plančak, University of Novi Sad, Serbia Brian Prasad, California Institute of Technology, Pasadena, USA Bernd Sauer, University of Kaiserlautern, Germany Brane Širok, UL, Faculty of Mech. Engineering, Slovenia Leopold Škerget, UM, Faculty of Mech. Engineering, Slovenia George E. Totten, Portland State University, USA Nikos C. Tsourveloudis, Technical University of Crete, Greece Toma Udiljak, University of Zagreb, Croatia Arkady Voloshin, Lehigh University, Bethlehem, USA President of Publishing Council Jože Duhovnik UL, Faculty of Mechanical Engineering, Slovenia General information Strojniški vestnik – Journal of Mechanical Engineering is published in 11 issues per year (July and August is a double issue). Institutional prices include print & online access: institutional subscription price and foreign subscription €100,00 (the price of a single issue is €10,00); general public subscription and student subscription €50,00 (the price of a single issue is €5,00). Prices are exclusive of tax. Delivery is included in the price. The recipient is responsible for paying any import duties or taxes. Legal title passes to the customer on dispatch by our distributor. Single issues from current and recent volumes are available at the current single-issue price. To order the journal, please complete the form on our website. For submissions, subscriptions and all other information please visit: http://en.sv-jme.eu/. You can advertise on the inner and outer side of the back cover of the magazine. The authors of the published papers are invited to send photos or pictures with short explanation for cover content. We would like to thank the reviewers who have taken part in the peerreview process.

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Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11 Contents

Contents Strojniški vestnik - Journal of Mechanical Engineering volume 58, (2012), number 11 Ljubljana, November 2012 ISSN 0039-2480 Published monthly

Papers Samo Venko, Boris Vidrih, Erik Pavlovič, Sašo Medved: Enhanced Heat Transfer on Thermo Active Cooling Wall 623 Jiang Ding, Yangzhi Chen, Yueling Lv: Design of Space-Curve Meshing-Wheels with Unequal Tine Radii 633 Ranko Božičković, Milan Radošević, Ilija Ćosić, Mirko Soković, Aleksandar Rikalović: Integration of Simulation and Lean Tools in Effective Production Systems – Case Study 642 Robert Iacob, Diana Popescu, Peter Mitrouchev: Assembly/Disassembly Analysis and Modeling Techniques: A Review 653 Baoping Cai, Yonghong Liu, Congkun Ren, Aibaibu Abulimiti, Xiaojie Tian, Yanzhen Zhang: Probabilistic Thermal and Electromagnetic Analyses of Subsea Solenoid Valves for Subsea Blowout Preventers 665 Dražen Bajić, Luka Celent, Sonja Jozić: Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control 673 Oğuz Çolak: Investigation on Machining Performance of Inconel 718 under High Pressure Cooling Conditions 683

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632 DOI:10.5545/sv-jme.2012.436

Enhanced Heat Transfer on Thermo Active Cooling Wall Venko, S. – Vidrih, B. – Pavlovič, E. – Medved, S. Samo Venko1,* – Boris Vidrih2 – Erik Pavlovič1 – Sašo Medved2 2 University

1 Hidria IMP Klima d.o.o., Slovenia of Ljubljana, Faculty of Mechanical Engineering, Slovenia

In the article a study of the cooling potential of thermo activated wall in an office building with enhanced convective heat transfer is presented. Heat transfer on a vertical cooled wall is enhanced by a longitude jet of supply fresh air from diffuser mounted parallel on the top of the wall. Such a system is compared to an adequate system with natural convection heat transfer from the cooled surface. Empirical models in the form of multicriterial polynoms for local and average convective heat transfer coefficients determination were developed for natural and enhanced convection using CFD techniques. Empirical models were used in the TRNSYS simulation tool for analyzing cooling potential increasing in the case of enhanced heat transfer on a cooled wall surface in a typical office. Results show a significant increase of the cooling load, a decrease of energy consumption for cooling of the office and better adaptive thermal comfort if heat transfer is enhanced with longitude jet of fresh supply air. Keywords: free cooling, thermo active building systems, enhanced convection heat transfer, thermal comfort, numeric heat transfer

0 INTRODUCTION Regarding expected climate changes, microclimate conditions in urban areas, the trend of population ageing, the energy consumption for the cooling of the buildings will be very important for ensuring the indoor thermal comfort as well as for approaching the near zero energy buildings in the near future [1] and [2]. In addition to architecture measures, free cooling offers a significant potential for the decrease of energy demand in the buildings. Such systems can be constructed in the form of a thermo active building system (TABS) and has recently become widely used for buildings cooling because of their undisputed advantages. Advantages are most recognized in office buildings with high cooling demands. Kalz et al. [3] describe TABS as a building construction elements thermally activated by water or air driven systems that operate with small temperature differences between indoor air and heating ventilating and air conditioning HVAC system supply temperatures. This enables the use of low exergy heating and cooling sources like ground water, borehole heat exchangers, earth-to-air heat exchangers, cooling towers and solar collectors. Optimal designed TABS in low-energy demand office buildings can provide a thermal comfort which meets 10% PPD even without mechanical cooling. Kalz et al. report a decrease of energy consumption by 50% in low energy buildings designed with TABS. Lehmann et al. [4] showed for office building cooled by thermally active concrete slab with a thickness of 300 mm that maximal cooling load up to 53 W/m2 can be achieved if maximal permissible daily indoor air temperature amplitude of 5 K can be tolerated. Koschenz and Dorer [5] studied a relation between heat loads and indoor air temperature in the room with

thermal activated concrete slab. Košir et al. found that the usage of cooling wall panels coupled with optimal surface temperatures results in considerable energy reduction and better indoor comfort [6]. Henze et al. [7] made a study about energy consumption and thermal comfort in buildings with all air systems and air systems combined with TABS for cooling of an office building. They point out that the operation of TABS and air conditioning must be synchronized to ensure energy efficient cooling. If so, the TABS heat sink was fairly constant at 30 W/m2 during cooling season and 20% less primary energy is needed compared to all the air system. Cooling with TABS also contributes to better indoor thermal comfort. During the summer all the air system was associated with a fairly constant PMV value of 0.75, comparing 0.56 for the combined system. This results in 12% instead of 17% PPD. Dovjak et al. found [8] that energy usage for cooling is by 41 to 62% lower for high surface temperature cooling ceiling systems comparing conventional cooling systems at similar thermal comfort. In all of the presented research, natural convection heat transfer was assumed. Since contemporary nonresidential buildings are all mechanically ventilated, forced air movement caused by ventilation system can be used for enhanced heat transfer on TABS surfaces resulting in mixed convection heat transfer. Kobus and Wedekind [9] defined mixed convection as the mode of convective heat transfer which is neither dominant by forced convection nor natural convection, but it is a combination of those two regimes. Yang and Panel [10] studied mixed convection heat transfer on vertical wall caused by downwards and upwards air jets. Upward jet flows were either aiding flows, if ϑw > ϑSA, either opposing flows when ϑw < ϑSA. Angirasa [11]

*Corr. Author’s Address: Hidria IMP Klima d.o.o., Godovič 150, SI-5275 Godovič, Slovenia, samo.venko@hidria.com

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Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632

found that upwards plan air jet over a hotter wall is identical to the downward air jet over the colder wall. Mokni et al. [12] studied assisted upward plane air jets with laminar and parabolic uniform velocity discharge profile. They found that discharge velocity profile highly affects convection only in jet zone. Neiswanger et al. [13] set a model for an average heat transfer coefficient for mixed convection as a general relation between natural and forced convection. This model enables determination of forced convection increase of average heat transfer coefficient. Awbi and Hatton [14] carried out experiments with a jet over an enclosure heated surfaces representing small room with interior dimensions 2.78×2.78×2.3 m. Neiswanger model for mixed convection and developed empirical models for an average heat transfer coefficients for forced convection supplement of mixed convection was used. Models are based on measured average heat transfer coefficients for mixed convection and empirical models for an average heat transfer coefficient of natural convection from their previous research [15]. Goldstein and Novoselac [16] studied mixed convection on vertical surfaces generated by ceiling slot diffusers. Their study shows that temperature difference between surface and supply air does not affect average convective heat transfer rate from cooled vertical wall. An average convective heat transfer is also independent of diffuser distance from the wall if distance is less than 23 cm. The presented research results in enhanced convective heat transfer caused by plane wall air jet have shown that heat transfer from TABS surface could be significantly enlarged. Authors mainly analyze average convective heat transfer coefficient at specific

boundary conditions, but no research on enhanced local heat transfer coefficient on thermal activated cooling wall by longitude jet of fresh supply air was found. In the presented study empirical expressions of local and average convective heat transfer coefficient on thermal activated cooling wall (TACW) in the case of natural and enhanced convection heat transfer were developed. Those expressions were afterwards used for modeling of energy demand and indoor thermal comfort in a typical office room cooled with TACW and compared to the free cooling systems without enhanced heat transfer. 1 MODELING OF LOCAL AND AVERAGE CONVECTIVE HEAT TRANSFER COEFFICIENT ON TACW IN CASE OF NATURAL AND ENHANCED CONVECTION 1.1 Natural Convection on TACW Computational fluid dynamic (CFD) tools is nowadays widely used owing to their user friendliness and wide range of validation. In the presented research Ansys Fluent 13.0 code was used for CFD simulation of temperature, pressure and velocity filed in selected office. Two-dimensional room space with length of 5 m and height of 3 m, presented in Fig. 1. was assumed to speed up the numerical solutions. Natural convection heat transfer was analyzed over TACW having constant surface temperature boundary condition. Surface temperature was maintained at ϑTACW = 20 °C. The opposite wall was supposed to be heat source emit uniformly convective heat flux between 2.5 and 63 W/m2. Convection was only heat transfer mechanize taken into account on all surfaces.

• • • • • •

TACW: ϑTACW = 20 °C, ∂ϑTACW / ∂x= 0.

Heat source wall: 2.5 ≤ q''w ≤ 63 W/m2, ∂ϑWall / ∂x = 0. Floor, Ceiling: q'' = 0 W/m2, ∂ q'' / ∂y = 0.

Fig. 1. Geometry of 2D office room model and boundary conditions used in numerical simulations for natural convection heat transfer from TACW

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Venko, S. – Vidrih, B. – Pavlovič, E. – Medved, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632

High density orthogonally meshes were used and we were focused on very fine mesh at TACW surface. The thickness of the first cell at the wall boundary was 0.14 mm, each neighbor layers was increased by the factor 1.08 comparing the previous one. The domain was divided into 114,660 elements with maximal mesh skewness 0.3 and minimal orthogonal of 0.97 which allow high quality of numerical solution. The mesh was tested with mesh independent criteria because the worst strategy would be to avoid this subject and to provide numerical simulations on a single computational grid [17]. Following settings of Ansys Fluent solver were used: double precision, k-omega viscosity model: SST, disabled radiation, incompressible ideal gas, coupled pressure-velocity field, last squares cell based gradient, PRESTO pressure model, second order upwind momentum, second order upwind turbulent kinetic energy, specific dissipation rate and energy model, explicit relaxation factors for momentum (0.3) and pressure (0.5), underrelaxation factors for density (0.6), body forces (1), turbulent kinetic energy (0.5), specific dissipation rate (0.5), turbulent viscosity (0.7) and energy (1), residual for continuity (0.0026), x-velocity (0.0001), y-velocity (0.0001) and energy (1×10−7). Steady state conditions were assumed. From local convective surface heat flux q''TACW ( x) the local convective heat transfer coefficient was determined:

C = –1.374 ∙ 10-4 ∙ (Δϑ)5 + 9.1717 ∙ 10-3 ∙ (Δϑ)4 – – 0.21987 ∙ (Δϑ)3 + 2.2566 ∙ (Δϑ)2 – – 9.1091 ∙ Δϑ + 26.2996, 0 m ≤ x ≤ 1.5 m,

C = –3.19 ∙ 10-5 ∙ (Δϑ)4 + 8.995 ∙ 10-4 ∙ (Δϑ)3 – – 8.5331 ∙ 10-3 ∙ (Δϑ)2 – 0.03632 ∙ Δϑ – 4.456, 1.5 m ≤ x ≤ 3 m.

The Eqs. (3) and (4) are valid for 2 ≤ Δϑ ≤ 20 °C, for the closed room with dimensions presented in Fig. 1 and room without any forced air movement. In Fig. 2 approximated local convective heat transfer coefficient hTACW over TACW for temperature differences 2.5 ≤ Δϑ ≤ 20 °C are plotted. Three sub regions regarding to heat transfer coefficient can be noticed: ceiling region at distance 0 < x ≤ 0.5 m, mid region 0.5 < x ≤ 2.5 m and the floor region at 2.5 < x ≤ 3 m. Heat transfer coefficient is the largest and most dependent on temperature difference Δϑ at the ceiling region and significantly decreases with an increase of the room high. In mid region heat transfer coefficient is fairly constant and almost independent of the distance from the ceiling. At floor region convective heat transfer coefficient sharply decreases and reaches minimal value of 0.28 W/(m2K) for all analyzed temperature differences.

hc(x) = q''TACW ( x) / Δϑ . (1)

Temperature difference Δϑ presents temperature difference between an average room air temperature and TACW surface temperature:

Δϑ = ϑi – ϑTACW . (2)

Average convective heat transfer coefficient hc,avg can be calculated from the known average surface heat flux q''c,avg Eq. (1) and we approximated it with Eq. (3) meanwhile the local convective heat transfer coefficient on TACW is approximated with Eq. (4):

hc,avg = 0.609 ∙ ln(Δϑ) + 1.182 ,

(3)

hc(x) = A + Be-C∙x, (4)

where functions A, B and C are equal to:

A = 0.52503 ∙ ln(Δϑ) + 1.3515,

B = 0.91764 ∙ ln(Δϑ) + 1.2844,

0 m ≤ x ≤ 3 m, 0 m ≤ x ≤ 1.5 m,

B = 1.0332 ∙ 10-11 ∙ (Δϑ)4 – 5.0926 ∙ 10-10 ∙ (Δϑ)3 + + 3.544 ∙ 10-9 ∙ (Δϑ)2 + 1.4908 ∙ 10-7 ∙ Δϑ – 1.987 ∙ 10-6, 1.5 m ≤ x ≤ 3 m,

Fig. 2. Approximated local heat transfer coefficient for natural convection on TACW for temperature difference 2.5 ≤ Δϑ ≤ 20 °C

A comparison between numerical results and approximated values due Eqs. (3) and (4) for selected cases is presented in Fig. 3 and shows good agreement between approximated and numerical results. To the best knowledge of the authors, no model of local temperature dependent convective heat transfer coefficient on TACW has been reported; only average convective heat transfer coefficient model from our

Enhanced Heat Transfer on Thermo Active Cooling Wall

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Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632

b) Fig. 3. Comparison between a) average hc,avg and b) local hc (x) convective heat transfer coefficient determinate by approximation function and numerical results

study can be verified. ASHRAE [18] suggest the following approximation:

hc,avg =1.31 (Δϑ)0.33 , (5)

meanwhile Khalifa and Marshall [15] proposed a model, which is valid for temperature differences Δϑ lower than 5 K only:

hc,avg =1.983 (Δϑ)0.25. (6)

Fig. 4 shows an average heat transfer coefficient on TACW calculated for temperature differenced Δϑ in range of 2 to 10 °C using different models. It can be noticed that Khalifa and Marshall [19] model differ significantly regarding to present the study and the ASHRAE model and that results of the presented study are similar to the ASHRAE model up to Δϑ = 5 °C, with only small differences in case of larger temperature differences Δϑ. Therefore, it can be concluded that boundary conditions, meshing and solver settings in the presented numerical modeling is adequate. 1.2 Enhanced Convection on TACW An analysis of enhanced convective heat transfer by downwards plan air jet of fresh supply air was done with the code Ansys Fluent 13.0 using the same mesh, solver setting and boundary conditions as they were used in the case of natural convection. Only differences were applied for residual criteria: continuity (0.0001), x-velocity (0.0001), y-velocity (0.0001), Energy (10 ∙ 10-7). As in the previous case, steady state conditions were assumed. 626

Fig. 4. Average convection heat transfer hc,avg coefficient for natural convection on TACW calculated using different models (3), (5) and (6)

The fresh air is supplied through the ceiling slot having width w equal to 10 mm and installed at the top of the TACW (at x = 0) as it is shown in Fig. 5. Velocities vSA of supply air, having constant temperature ϑSA = 27 °C, were selected in the range between 1 and 4 m/s. Surface temperature of TACW was varied in range of 17 ≤ ϑTACW ≤ 26 °C and the difference between wall temperature and supply air temperature in the range of –10 ≤ Δϑ ≤ –1 °C. Minimum supply air velocity vSA = 1 m/s was selected according to a minimal amount of fresh air, maximal velocity vSA = 4 m/s according to the good practice where higher velocity causes discomfort in ventilated rooms. Reject air was extracted through the opening in the ceiling with the same flow rate. The position of the outlet opening was selected by numerical simulations

Venko, S. – Vidrih, B. – Pavlovič, E. – Medved, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632

• • • • • •

TACW: ϑTACW = 20 °C, ∂ϑTACW / ∂x= 0.

Heat source wall: q''w = 30 W/m2,

∂ q'' / ∂x = 0.

Floor, Ceiling: q'' = 0 W/m2, ∂ q'' / ∂y = 0.

Fig. 5. Geometry of 2D office room model and boundary conditions used in numerical simulations for modeling of enhanced convection heat transfer over TACW

in the way not to influence heat transfer on TACW. Using reference temperature difference proposed by Spitler et al. [20] and [21]:

Δϑ = ϑSA – ϑTACW , (7)

and average surface heat flux q''c,avg Eq. (1) over TACW, enhanced average convective heat transfer coefficient hc,avg was approximated with Eq. (8) and local convective heat transfer coefficient over TACW with Eq. (9). From numerical results it was found that reference temperature difference has no influence on the convective heat transfer on TACW and therefore convective heat transfer coefficients can be approximated as a function of vSA only. The same conclusion was reported by Goldstein and Novoselac [16].

hc,avg = 2.1547 ∙ vSA + 0.9942 ,

(8)

hc (x) = A + Be(C∙x + D) ,

(9)

shown in Fig. 6. It can be noticed that heat transfer coefficients decrease regarding the distance along the TACW and increase with supply air velocity.The approximated values of average and local convective heat transfer coefficients were compared to numerical solutions in Fig. 7. All numerical simulations are included for hc,avg and the selected case is presented for hc (x).

where functions A, B, C and D are equal to:

A = 0.2333 ∙ vSA + 0.3667 ,

B = 1.3429 ∙ ln(vSA) + 1.6261 ,

C = – 0.082966 ∙ vSA – 0.37768 ,

D = –6.5643 ∙ 10-3 ∙ vSA5 + 0.13796 ∙ vSA4 – – 1.0324 ∙ vSA3 + 3.53468 ∙ vSA2 – 5.2852 ∙ vSA + 3.9115. Approximation functions (8) and (9) are valid for slot width w = 0.01 m, 1 ≤ vSA ≤ 4 m/s, 2 ≤ Δϑ ≤ 20 °C and for a closed room. Approximated enhanced local convection heat transfer coefficient is

Fig. 6. Local heat transfer coefficients for mixed convection on cooled wall for 1 ≤ vSA ≤ 4 m/s calculated due to (9)

3 THERMAL RESPONSE OF OFFICE COOLED WITH TACW Cooling of the typical office with natural and enhanced convection on TACW was studied using the TRNSYS simulation tool [22] and climate data from the Test Reference Year (TRY) for Ljubljana, Slovenia [23]. The office with dimensions of 5×6×3 m

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b) Fig. 7. Comparison between approximated and numerical determinated values for a) average hc,avg and b) local hc (x)

shown in Fig. 8 has one external wall, meanwhile all other walls, the floor and the ceiling were treated as externally adiabatic walls allowing only internal side heat accumulation. The external wall, with heat transfer coefficient U = 0.2 W/(m2K), has a window with Uwin = 0.7 W/(m2K) in half size of the wall. External window shading is activated when solar radiation on horizontal plane exceeds 300 W/m2. Surface temperature of TACW was maintained at constant temperature ϑTACW = 17 °C. Such surface temperature could, for example, be achieved with mine water at source temperature level ϑ = 12.8 °C [26]. The office is mechanically ventilated through the ceiling slot opening positioned at the top of the TACW. The slot is 0.01 m wide with length equal to TACW’s length 3 m (Fig. 8a) or (Fig. 8b). In all the cases fresh outdoor air flow rate was maintained at 216 m3/h in occupied hours (7 AM to 18 PM, Monday to Friday) to provide minimal hygienic requirements of 2 l/(s ∙ m2floor) for the offices - Classification A according

to CR 1752 : 1998 [24]. During the unoccupied hours the air exchange rate was reduced to 0.2 l/h [25]. Supply air passed the heat recovery unit with an effectiveness of ∈ = 0.75 when ϑe > ϑi. The outlet ceiling slot was positioned at the top of opposite wall. It was found from CFD simulations that outlet ceiling slot does not influence convective heat transfer on TACW if it is more than one half of room length away from TACW.Three levels of internal heat gains were assumed [27]: light level 30 W/m2, medium level 45 W/m2 and high level 60 W/m2. Natural convection and enhance convection over TACW were calculated by using empirical models Eqs. (4) and (9) for local convection heat transfer coefficient developed with CFD. Hour-by-hour thermal response calculation of office room was used for determining the efficiency of free cooling based on the acceptance of indoor environment conditions in none mechanical cooled space.

Fig. 8. Analyzed office room with designation of surfaces: a) LTACW = 3 m , b) LTACW = 6 m

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Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 623-632

3.1 Operating Scenarios Eight scenarios which were analyzed differ regarding ventilation strategies and the type of convection over TACW. For the first scenario the office without free cooling and mechanical ventilation with outdoor air was assumed. The second scenario was similar, but with additional night cooling with outdoor air with two air changes per hour (ACH = 2 h-1) during the unoccupied hours. This scenario was extended in the scenarios A3, A6, B3, B6, C3 and D3 with additional free cooling of the office using TACW. In scenarios B3, C3, D3 the length of TACW was 3 m and in scenarios A6 and B6 the length of TACW was 6 m. In the scenarios A3 and A6 natural convection on TACW was presumed, in all other scenarios convection on TACW was enhanced with supply air jet flow. In some scenarios (B6, C3, D3) we considered using induction VAV terminal [28] which enhanced jet flow velocity without additional fan. Maximal induction ratio 1 was assumed. This results in doubled inlet air flow rate. Enhanced nighttime natural ventilation with ACH = 2 h-1 was assumed when indoor air temperature excided 22 °C and outdoor air temperature was 3 K lower of indoor air temperature. Table 1. Various scenarios predicted in office thermal response calculations Scenario: Length of TACW, LTACW [m] Natural convection Jet flow enhanced convection Outdoor airflow rate in occup. hours, qv,e [m3/h] Supply airflow rate in occupied hours, qv,SA [m3/h] Supply air velocity, vSA [m/s]

A3 3 +

A6 6 +

B3 3

B6 6

C3 3

D3 3

216 216 216 216 216 216 216 216 216 432 324 432 0

4 RESULTS AND DISCUSSION Cooling efficiency was analyzed at the base of cooling degree hour (CDH) as product of ‘time when indoor operative temperature exceeds reference temperature’ and ‘temperature difference between exceeded indoor operative temperature and reference temperature’ [29]:

∑ (ϑ N

j =1

i, j

− ϑref

)

, (10)

where j is the hour-to-hour calculated operative temperature as the arithmetical mean of the indoor air temperature and surface temperature, ϑref is reference temperature and N is the number of hours during the

summer period. Sign “+” indicates that only positive values are taken into account in summation. As reference operative temperature, the adaptive indoor temperature was used regarding outdoor temperature, “alpha” building parameters set by Linden et al. [30] and Class A thermal comfort (90% acceptance):

ϑe > 12 °C: ϑref = 20.3 °C + 0.31 ∙ ϑe , (11)

ϑe < 12 °C: ϑref = 22.7 °C + 0.11 ∙ ϑe . (12)

Results are presented in Figs. 9 and 10 for two different internal heat gains values – for mid and high level. The analyzes shows that in case of office without TACW (scenario 1 and scenario 2), required thermal indoor comfort, indicated by CDH equal or less to zero cannot be ensured even in case of low internal gains ( q''IGH = 30 W/m2). At LTACW = 3 m mechanical cooling could be avoided only with enhanced convection in the case of medium internal gains. Enhanced convection with higher air jet velocities reduces overheating to CDH = 5 K h/year for scenario C3 (vSA = 3 m/s) and to only CDH = 0.3 K h/year for scenario D3 (vSA = 4 m/s). At medium level of internal gains natural convection even at LTACW = 6 m (scenario A6) cannot ensure suitable thermal comfort comparing enhanced convection which at the same length of TACW (scenario B6) satisfies adaptive thermal comfort criteria Class A. Enhancing heat transfer with higher air jet velocities at LTACW = 3 m does not bring satisfactory lower indoor operative temperatures at high level of internal heat gains. CDH = 114 K h/year is still too high for acceptable thermal indoor comfort in scenario D3 despite air jet velocity vSA = 4 m/s (Fig. 10). However, on the another hand the same amount of supply air is used in scenario B6 (LTACW = 6 m, vSA = 2 m/s), which is suitable to meet the thermal indoor comfort criteria in Class A at q''IGH = 60 W/m2. 5 CONCLUSIONS Cooling with thermo active building systems with natural convection enable noiseless operation, however cooling potential strongly depends on temperature differences between surface and adjacent air temperature. Cooling with natural convection is not easy to control and adapt to the current loads. Lowering of the TACW temperature could lead to thermal discomfort and surface condensation. Such cases can be significantly improved if convection is enhanced by supply air wall jet. This allows controlling heat transfer on TACW with slot velocity

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and also with a difference between supply air temperature and surface temperature.

at acceptable: CDH = 8 K h/year. From the results it can be concluded that the size of TACW surface can be significantly reduced if convective heat transfer is enhance by the supply air wall jet. 6 NOMENCLATURE List of symbols ACH CDD CDH Δ

∈

Fig. 9. CDH for the office with internal heat gains of 45 W/m2

Air Changes per Hour Cooling Degree Days Cooling Degree Hours difference heat recovery efficiency

g h L qv q” R2 ϑ σ U v x y CFD HVAC

gravity heat transfer coefficient length volumetric airflow rate heat flux Pearson correlation coefficient temperature in Celsius standard deviation overall heat transfer coefficient velocity stream wise coordinate transverse coordinate Computational Fluid Dynamic Heating Ventilating and Air Conditioning PMV Predicted Mean Value PPD Percentage of People Dissatisfied TABS Thermo Active Building Systems TACW Thermo Active Cooling Wall TRY Test Reference year VAV Variable Air Volume

[1/h] [K day/year] [K h/year] [%] [m/s2] [W/(m2 K)] [m] [m3/h] [W/m2] [/] [°C] [W/(m2 K)] [W/(m2 K)] [m/s] [m] [m]

Subscripts Fig. 10. CDH for the office with internal heat gains of 60 W/m2

It was shown that in the case of enhanced convection with initial slot velocity (vSA = 2 m/s) light level of internal heat gains can be easily covered with only 3 m of TACW. Additionally, at mid-level of internal heat gains enhanced mixed convection with slot velocity (vSA = 4 m/s) practically meets Class A requirements for adaptive comfort criteria with a little, almost unrecognizable overheating: CDH = 0.3 K h/year at only LTACW = 3 m. Natural convection is not able to cover those internal gains even at LTACW = 6 m. Here, the benefit of mixed convection can be seen. High level of internal gains (60 W/m2) can be covered only with mixed convection at LTACW = 6 m 630

avg app c e floor i IHG j N num ref SA w win 3 6

average approximation convection outdoor floor indoor Internal Heat Gains hour-to-hour calculated operative temperature number of TRY hours Value based on numerical simulation reference value Supply Air wall window length of TACW: 3 m length of TACW: 6 m

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7 ACKNOWLEDGEMENT This study was partially financed by the European Union, European Social Fund. 8 REFERENCES [1] Vidrih. B., Medved. S. (2008). The effect of changes in the climate on the energy demands of buildings. International Journal of Energy Research, vol. 32, no. 11, p. 1016-1029, DOI:10.1002/er.1410. [2] Vidrih, B., Dolinar, M., Medved, S. (2006). The connection between the climate model and a building’s thermal response model: a case of Slovenia. Strojniški vestnik - Journal of Mechanical Engineering, vol. 52, no. 9, p. 568-586. [3] Kalz, D., Pfafferott, J., Herkel, S. (2006). Monitoring and data analysis of two low energy office buildings with a thermo-active building system (TABS). AIVC27th conference – EPIC 2006 AIVC “Technologies & sustainable policies for a radical decrease of the energy consumption in buildings”, p. 217-222. [4] Lehmann, B., Dorer, V., Koschenz, M. (2007). Application range of thermally activated building systems TABS. Energy and Buildings, vol. 39, no. 5, p. 593-598, DOI:10.1016/j.enbuild.2006.09.009. [5] Koschenz, M., Dorer, V. (1999). Interaction of an air system with concrete core conditioning. Energy and Buildings, vol. 30, no. 2, p. 139-145, DOI:10.1016/ S0378-7788(98)00081-4. [6] Košir, M., Krainer, A., Dovjak, M., Perdan, R., Kristl, Ž. (2010). Alternative to the Conventional Heating and Cooling Systems in Public Buildings. Strojniški vestnik – Journal of Mechanical Engineering, vol. 56, no. 9, p. 575-583. [7] Henze, G.P., Felsmann, C., Kalz, D.E., Herkel, S. (2008). Primary energy and comfort performance of ventilation assisted thermo-active building systems in continental climates. Energy and Buildings, vol. 40, no. 2, p. 99-111, DOI:10.1016/j.enbuild.2007.01.014. [8] Dovjak, M., Shukuya, M., Krainer, A. (2012). Exergy analysis of conventional and low exergy systems for heating and cooling of near zero energy buildings. Strojniški vestnik – Journal of Mechanical Engineering, vol. 58, no. 7-8, p. 453-461, DOI:10.5545/svjme.2011.158. [9] Kobus, C.J., Wedekind, G.L. (1996). Modeling the local and average heat transfer coefficient an isothermal vertical flat plate with assisting and opposing combined forced and natural convection. International Journal of Heat and Mass Transfer, vol. 39, no. 13, p. 2723-2733, DOI:10.1016/0017-9310(95)00360-6. [10] Yang, J. W., Patel, R. D. (1973). Effect of buoyancy on forced convection in a two -dimensional wall jet along a vertical wall. Journal of Heat Transfer, vol. 95, no. 1, p. 121-123, DOI:10.1115/1.3449980. [11] Angirasa, D. (2000). Mixed convection in a vented enclosure with isothermal vertical surface. Fluid

Dynamics Research, vol. 26, no. 4, p. 219-233, DOI:10.1016/S0169-5983(99)00024-6. [12] Mokni, A., Kechiche, J., Mhiri, H., Le Palec, G., Bournot, P. (2009). Inlet conditions effects on vertical wall jets in forced and mixed convection regimes. International Journal of Thermal Science, vol. 48, no. 10, p. 1884-1893, DOI:10.1016/j. ijthermalsci.2009.02.021. [13] Neiswanger, L., Johnson, G.A., Carey, V.P. (1987). An experimental study of high Rayleigh number mixed convection in a rectangular enclosure with restricted inlet and outlet openings. Journal of Heat Transfer, vol. 109, no. 2, p. 446-453, DOI:10.1115/1.3248102. [14] Awbi, H.B., Hatton, A. (2000). Mixed convection from heated room surfaces. Energy and Buildings, vol. 32, no. 2, p. 153-166, DOI:10.1016/S0098-8472(99)000635. [15] Awbi, H.B., Hatton, A. (1999). Natural convection from heated room surfaces. Energy and Buildings, vol. 30, p. 233-244, DOI:10.1016/S0378-7788(99)00004-3. [16] Goldstein, K., Novoselac, A. (2010). Convective heat transfer in rooms with ceiling slot diffusers. HVAC&R Research, vol. 16, no. 5, p. 629-656, DOI:10.1080/1078 9669.2010.10390925. [17] Ternik, P., Rudolf, R. (2012). Heat transfer enhancement for natural convection flow of waterbased nanofluids in a square enclosure. International Journal of Simulation Modelling, vol. 11, no. 1, p. 2939, DOI:10.2507/IJSIMM11(1)3.198. [18] 2001 ASHRAE Handbook Fundamentals. (2001). ASHRAE, Atlanta. [19] Khalifa, A.J.N., Marshall, R.H. (1989). Natural and forced convection on interior building surfaces: preliminary results. Applied Research Conference, p. 249-257. [20] Spitler, J.D., Pedersen, C.O., Fisher, D.E., Menne, P.F., Cantillo, J. (1991). An experimental facility for investigation of indoor convective heat transfer. ASHRAE Transactions 97, vol. 1, p. 497-504. [21] Spitler, J.D., Pedersen, C.O., Fisher, D.E., Menne, P.F., Cantillo, J. (1991). Interior convective heat transfer in buildings with large ventilative flow rates. ASHRAE Transactions 97, vol. 1, p. 505-515. [22] TRNSYS, from http://www.trnsys.com, accessed on 2012-03-08. [23] Ministry of Agriculture and Environment – Slovenian Environment Agency, from http://meteo.arso.gov.si/ met/sl/climate/tables/test_ref_year, accessed on 201203-08. [24] CR 1752:1998 (1998). Ventilation for buildings – Design criteria for the indoor environment, European Standard. CEN, Brussels. [25] Rules on the ventilation and air-conditioning of buildings (2002). Official Gazzete of the Republic of Slovenia, vol. 42, p. 4139-4161. (in Slovene) [26] Božović, M. (2004). Report of pumping test at well FK-1 in Zagorje. Preliv d.o.o., Ljubljana. (in Slovene)

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[27] Corgnati, S.P., Kindinis, A. (2007). Thermal mass activation by hollow core slab coupled with night ventilation to reduce summer cooling loads. Building and Environment, vol. 42, no. 9, p. 3285-3297, DOI:10.1016/j.buildenv.2006.08.018. [28] HC Barcol-Air, from http://www.barcol-air.nl/PDF%20 documentatie/VAV%20CAV%20documentation%20NV. pdf, accessed on 2012-03-08. [29] Papakostas, K., Kyriakis, N. (2005). Heating and cooling degree-hours for Athens and Thessaloniki,

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Greece. Renewable Energy, vol. 30, no. 12, p. 18731880, DOI:10.1016/j.renene.2004.12.002. [30] Van der Linden, A.C., Boerstra, A.C., Raue, A.K., Kurvers, S.R., de Dear, R.J. (2006). Adaptive temperature limits: A new guideline in The Netherlands: A new approach for the assessment of building performance with respect to thermal indoor climate. Energy and Buildings, vol. 38, no. 1, p. 8-17, DOI:10.1016/j.enbuild.2005.02.008.

Venko, S. – Vidrih, B. – Pavlovič, E. – Medved, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 633-641 DOI:10.5545/sv-jme.2012.493

Design of Space-Curve Meshing-Wheels with Unequal Tine Radii Ding, J. –Chen, Y. –Lv, Y. Jiang Ding –Yangzhi Chen* –Yueling Lv

South China University of Technology, China In some recent papers a new gear mechanism named Space-Curve Meshing-Wheel (SCMW) has been proposed by the present authors. However, the research presented was limited in the equal tine radius case. This paper presents a method to solve the SCMW design with unequal tine radii. As a consequence, with a pair of contact curves, the tine radii of the driving and driven wheels can be selected independently according to actual need. A design example is illustrated in detail and testified in both simulation and practical experiment. This method provides a design fundamental for the SCMWs to optimize the tine shapes according to strength conditions, and therefore it can extend their application in industrial. Keywords: gear, Space-Curve Meshing-Wheel, unequal tine radius, contact curve

0 INTRODUCTION A gear mechanism named Space-Curve MeshingWheel (SCMW) was invented by Chen et al. [1] to [3]. The SCMW is based on the theory of space curve meshing instead of traditional space surface meshing [4] to [8]. Space curve meshing is a transmission through continuous point contacts between two conjugate curves. With a large transmission ratio, small size and light weight, SCMW is highly convenient to be applied in the transmission between two intersecting axes in the small space inside micro machines. After recent research on space curve meshing equations [1] to [3], contact ratio [9], design criterion [10] and manufacture technology [11], the SCMW has possessed an integrated application like micro reducers [12]. However, the research published was limited in the equal tine radius case. Furthermore, the space curve meshing equations obtained at the meshing point were relevant to the tine radii, and therefore the wheel pair of the SCMW must be in a one-toone correspondence. But in practical application, the demanding tine radii of the driving and driven wheels are not always the same. The tine radii depend on the demanding strength corresponding to their working conditions. If the tine radii of the driving and driven wheels are irrelevant from each other, they can be designed independently. This paper presents a design method to make the tines of SCMW irrelevant in the unequal tine radius case. To testify the method, an example is designed, and both simulation and practical experiment are carried out with the same data in the example. 1 DESIGN FUNDAMENTAL The essence of the space-curve meshing is transmission through continuous point contacts

between two conjugate curves [1]. To provide contact curves smooth and slight objectives like tines, for instance, should be designed.

Fig. 1. Cylindrical tines and contact curves

For reasons of simplicity, cylindrical tines have been adopted in this paper as in previous papers [2] to [3]. As shown in Fig. 1, two invariant circles are tangent at the meshing point each moment. The circle centers are along the contact vector direction and at the opposite sides of the meshing point (indicated as –γ1 and γ1 in Fig. 1). After the curves finish the whole meshing, point after point, the two circles form the cylindrical shapes of the driving and driven tines, respectively. In Fig. 1, M is the meshing point at each moment, while M(1) and M(2) are the corresponding points at the driving and driven tines, respectively. The point set of M(1) is the driving contact curve; the point set of M(2) is the driven contact curve. According to the design depicted above, for the same contact curves, the driving and driven tines can adopt circles with different radii, attaining the cylindrical tines with different radii. Even the tines with variable radii can be designed in this way. As the

*Corr. Author’s Address: School of Mechanical and Automotive Engineering, South China University of Technology, Wushan RD.,Tianhe District, Guangzhou, China, meyzchen@scut.edu.cn

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circles are always in opposite directions at the meshing point, the driving and driven tines will be irrelevant from each other. In theory, the radii of the tines are free to choose as long as there is enough room. In practical application, the tine radii are determined according to the strength conditions. 2 DESIGN METHOD

 cos ϕ1  − sin ϕ 1 M o1 =   0   0

The transformation matrix from o1 – x1 y1 z1 to o2 – x2 y2 z2 is as Eq. (2) [13].

2.1 Space Meshing Coordinates The equations of the contact curves and the center curves are all calculated in the space meshing coordinates, which are established as Fig. 2. The fixed coordinates for the driving and driven wheels are given as o – x y z and op – xp yp zp , respectively. Planes xp op zp and x o z are in the same plane. Denote the distance from point op to axis z as a and the distance to axis x as b. Included angle between axis z and axis zp is (π–θ), where θ is the included angle between the angular velocity vectors of the driving and driven wheels. o1 – x1 y1 z1 and o2 – x2 y2 z2 are relatively static with the driving and driven wheels. They are rotating coordinates with respect to o – x y z and op – xp yp zp , respectively. At the initial moment, o1 – x1 y1 z1 coincides with o – x y z , while o2 – x2 y2 z2 coincides with op – xp yp zp . At any moment, point o1 coincides with point o, and axis z1 coincides with axis z; point o2 coincides with point op, and axis z2 coincides with axis zp. After meshing begins, o1 – x1 y1 z1 rotates around axis z1, while o2 – x2 y2 z2 rotates around axis z2.

sin ϕ1 0 0  cos ϕ1 0 0  . (1) 0 1 0  0 0 1

M 21

 − cos ϕ1 cos ϕ 2 cos θ − sin ϕ1 sin ϕ 2  cos ϕ sin ϕ cos θ − sin ϕ cos ϕ 1 2 1 2 =  cos ϕ1 sin θ  0  − sin ϕ1 cos ϕ 2 cos θ + cos ϕ1 sin ϕ 2 sin ϕ1 sin ϕ 2 cos θ + cos ϕ1 cos ϕ 2 sin ϕ1 sin θ 0

− cos ϕ 2 sin θ sin ϕ 2 sin θ − cos θ 0

− a cos ϕ 2 cos θ + b cos ϕ 2 sin θ  a sin ϕ 2 cos θ − b sin ϕ 2 sin θ  . (2)  a sin θ + b cos θ  1 

As shown in Fig. 2, suppose: ϖ1 and ϖ2 are the angular velocities of the driving and driven wheels; φ1 and φ2 are the rotation angles of the driving and driven wheels after the meshing begins; i12 is the transmission ratio. The kinematic relations are obtained as Eqs. (3) and (4):

ϖ1 = i12 ϖ2 , (3)

φ1 = i12 φ2 . (4)

2.2 Kinematical Equation According to [1], the motion at the meshing point should satisfy the kinematical equation as Eq. (5):

Fig. 2. Space meshing coordinates

The transformation matrix from o1 – x1 y1 z1 to o – x y z is as Eq. (1) [13].

634

ν12·β = 0,

(5)

where ν12 is the relative velocity at the meshing point βx  between the driving and driven tines, and β =  β y  is    β z  the unit normal vector of the driving contact curve in o – x y z. Suppose that β(1) is the unit normal vector of the driving curve in o1 – x1 y1 z1. Considering Eq. (1), we get the equation of the unit normal vector as Eq. (6):

Ding, J. –Chen, Y. –Lv, Y.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 633-641

The relative velocity at the meshing point is as Eq. (9):

 β x(1) cos ϕ1 + β y(1) sin ϕ1    β =  − β x(1) sin ϕ1 + β y(1) cos ϕ1  . (6)   β z(1)  

ν12 = ν1 – ν2. (9)

Considering Eq. (1), we get:

The velocities at the meshing point of the driving and driven tines are as Eqs. (7) and (8):

 yM ϖ 1  v1 =  − xM ϖ 1  , (7)  0 

Substituting Eqs. (7), (8) and (10) into Eq. (9), relative velocity at the meshing point as Eq. (11) is obtained:

yM ϖ 2 cos θ    v2 =  − ( zM − b )ϖ 2 sin θ − ( xM + a )ϖ 2 cos θ  . (8)   yM ϖ 2 sin θ

(

 xM = xM(1) cos ϕ1 + yM(1) sin ϕ1  (1) (1)  yM = − xM sin ϕ1 + yM cos ϕ1 . (10)  (1)  zM = zM

)

  − xM(1) sin ϕ1 + yM(1) cos ϕ1 (ϖ 1 − ϖ 2 cos θ )    (1) (1) (1) (1) (1) v12 =  − xM cos ϕ1 + yM sin ϕ1 ϖ 1 + zM − b ϖ 2 sin θ + xM cos ϕ1 + yM sin ϕ1 + a ϖ 2 cos θ  . (11)   1 1 − − xM( ) sin ϕ1 + yM( ) cos ϕ1 ϖ 2 sin θ  

(

)

(

Substituting Eqs. (6) and (11) into Eq. (5), the kinematical equation at the meshing point as Eq.(12) is obtained:

(1)

β x − xM β y

(

(1)

) (ϖ

− ϖ 2 cos θ ) +

)

(1)

)

(

)

equation of the driving contact curve is given as Eq. (13):

+ aϖ 2 cos θ − β x sin ϕ1 + β y cos ϕ1 +

(

)

(

)

1 1 1 + zM( ) − b ϖ 2 sin θ β y ( ) cos ϕ1 − β x ( ) sin ϕ1 +

(

(1)

)

(

+ xM sin ϕ1 − yM cos ϕ1 ϖ 2 sin θ β z

(1)

) = 0. (12)

From Eq. (12) above, the relationship between φ1 and t can be gained, and then the equations of the contact curves and the center curves can be derived. As neither r1 nor r2 exists in Eq. (12), we can conclude that the kinematical equation is only related 1 to the properties of the driving contact curve ( xM( ) , 1 1 ( ) 1 ( ) 1 (1) ( ) yM , zM( ) , β x , β y and β z ) and the kinematic relations (a, b, θ, ϖ1, ϖ2, and φ1) between the driving and driven contact curves, but not the tine radii. 2.3 Equations of Contact Curves Denote the matrices of M(1) in o1 – x1 y1 z1 and M(2) in  xM( 2)   xM(1)   2  (1)  o2 – x2 y2 z2 as  yM  and  yM( )  , respectively. The  ( 2)   (1)   zM   zM 

)

 xM(1) = xM(1) ( t )  (1) (1)  yM = yM ( t ) . (13)  (1) (1)  zM = zM ( t )

Considering Eqs. (2) and (13), the equation of the driven contact curve as Eq. (14) can be obtained:  xM( 2) = ( − cos ϕ1 cos ϕ 2 cos θ − sin ϕ1 sin ϕ 2 ) xM(1) +  1  + ( − sin ϕ1 cos ϕ 2 cos θ + cos ϕ1 sin ϕ 2 ) yM( ) −  1 − cos ϕ 2 sin θ zM( ) − a cos ϕ 2 cos θ + b cos ϕ 2 sin θ   ( 2) (1)  yM = ( cos ϕ1 sin ϕ 2 cos θ − sin ϕ1 cos ϕ 2 ) xM +  1 . (14) + ( sin ϕ1 sin ϕ 2 cos θ + cos ϕ1 cos ϕ 2 ) yM( ) +   1 + sin ϕ 2 sin θ zM( ) + a sin ϕ 2 cos θ − b sin ϕ 2 sin θ   ( 2) (1) (1) (1)  zM = cos ϕ1 sin θ xM + sin ϕ1 sin θ yM − cos θ zM +  + a sin θ + b cos θ   

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2.4 Equations of Center Curves Denote γ and γ(1) as unit binormal vectors of the driving curve in o – x y z and o1 – x1 y1 z1, respectively. As shown in Figs. 1 and 3, at every meshing moment, if each meshing point M(t) moves a distance of r1 in the direction of –γ(1), the corresponding point in the driving center curve is obtained; if each meshing point M(t) moves a distance of r2 in the direction of γ(t), the corresponding point in the driven center curve is obtained. The tine radii as Eqs. (15) and (16) can be derived: uuuuur r1 ( t ) = −r1γ ( t ) = MM 1 , (15)

According to Eqs. (2) and (18), the equation of the driven center curves is as Eq.(20):  xM( 2)  2        ( 2)  yM 2         zM( 2)  2      

uuuuur r2 ( t ) = r2γ ( t ) = MM 2 . (16)  xM(1)   1 uuuuur Denote M1 and MM 1 in o1 – x1 y1 z1 as  yM(1)1  and    zM(1)   1

( ) () () + ( − sin ϕ cos ϕ cos θ + cos ϕ sin ϕ ) ( y + y )− () () − cos ϕ sin θ ( z + z )+

() = ( − cos ϕ1 cos ϕ 2 cos θ − sin ϕ1 sin ϕ 2 ) xM( ) + xMM + 2 2

1 M

1 MM 2

+ ( −a cos ϕ 2 cos θ + b cos ϕ 2 sin θ )

( ) () () + ( sin ϕ sin ϕ cos θ + cos ϕ cos ϕ ) ( y + y )+ + sin ϕ sin θ ( z ( ) + z ( ) ) +

() = ( cos ϕ1 sin ϕ 2 cos θ − sin ϕ1 cos ϕ 2 ) xM( ) + xMM + 2 1

1 M

1 MM 2

. (20)

+ ( a sin ϕ 2 cos θ − b sin ϕ 2 sin θ )

( ) () () + sin ϕ sin θ ( y + y )− () () − cos θ ( z + z ) + ( a sin θ + b cosθ )

() = cos ϕ1 sin θ xM( ) + xMM + 2 1

1 M

1 MM 2

(1)   xM( 2)   xMM 1  1   u uuuu r (1)   yMM , M2 and MM 2 in o2 – x2 y2 z2, as  yM( 21)  and 1     (1)   zM( 2)   zMM 1 1     ( 2)   xMM 2   ( 2)   yMM , respectively. 2   2) (  zMM  2  

The vector addition triangles are shown in Fig. 3. From Fig. 3, Eqs. (17) and (18) can be derived.

(1)   xM(1)   x (1)   xMM 1   1  M   (1)   yM(1)  =  yM(1)  +  yMM , (17) 1   1   (1)   1) 1) ( (  zM   zM   zMM   1  1 ( 2)

( 2)

 xM   x   xMM  2   2  M   ( 2)   yM( 2)  =  yM( 2)  +  yMM . (18) 2   2   ( 2)   2) 2) ( (  zM   zM   zMM  2    2 ( 2)

According to Eq. (17), the equation of the driving center curves is as Eq. (19): (1)

636

(1)

Fig. 3. Vector addition triangles

3 DESIGN EXAMPLE 3.1 Equation of Driving Contact Curve In the reference [1] to [3], a helix curve was given as an example. In comparison, the same curve is adopted as the driving contact curve, as shown in Fig. 4a. The Equation of M(1) in o1 – x1 y1 z1 is as Eq. (21):

(1)

 xM = xM + xMM 1  1  (1) (1) (1)  yM1 = yM + yMM1 . (19)  (1) (1) (1)  zM1 = zM + zMM1

 xM(1) = m cos t  (1) π   yM = m sin t  −π ≤ t ≤ −  , (21) 2   (1) π z = n + nt M 

where m is the helix radius of the driving curve; n is the pitch parameter of the driving curve, denoting the

Ding, J. –Chen, Y. –Lv, Y.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 633-641

pitch as p, n = p / 2π; t is the parameter indicating the scope of the helix curve. –π ≤ t ≤ –π / 2 means a quarter circle of the helix curve. When t = – π, the driving and driven tines begin to mesh; when t = –π / 2, the two tines begin to separate. The lengths of the driving and driven contact curves are directly controlled by the scope of t as needed.

Considering –π ≤ t ≤ –π / 2 and 0 < φ1, the relationship between φ1 and t can be deviced: φ1 = t + π . (25)

3.3 Equation of Driven Contact Curve According to Eqs. (4), (14), (21) and (25), the equation of M(2) in o2 – x2 y2 z2 is as Eq. (26): t +π  ( 2)  xM = ( m − a ) cos θ − ( nπ + nt − b ) sin θ  ⋅ cos i 12   ( 2) t +π . (26)  yM = − ( m − a ) cos θ − ( nπ + nt − b ) sin θ  ⋅ sin i12  2  zM( ) = − ( m − a ) sin θ − ( nπ + nt − b ) cos θ  

Obviously, Eq. (26) is a conical helix curve, as shown in Fig. 4b. 3.4 Equations of Center Curves According to Eqs. (15) and (16), the radii of the driving and driven tines are as Eqs. (27) and (28) in o1 – x1 y1 z1 .

Fig. 4. a) Driving and b) driven contact curves

(1)   xMM 1   (1)   yMM = − r1γ (1) , (27) 1   (1)   zMM  1

(1)   xMM 2   (1)   yMM = r2γ (1) . (28) 2   (1)   zMM 2  

The unit normal vector and the unit binormal vector of the driving curve are derived as Eqs. (22) and (23).

(1)

 β x(1)   − cos t    =  β y(1)  =  − sin t  , (22)  (1)     β z   0 

  γ x(1)      = γ y(1)  =  −  (1)   γ z    

n sin t 2

n +m n cos t 2

n +m m n2 + m2

     . (23)    

3.2 Kinematic Equation Substituting Eqs. (21) and (22) into Eq. (12), the kinematic equation as Eq. (24) is obtained :

ϖ 2 sin (ϕ1 − t )  a cos θ + ( nπ + nt − b ) sin θ  = 0. (24)

From Eqs. (19), (21), (23) and (27), the equation of the driving center curve is derived as Eq. (29):

 (1)  xM1 = m cos t −   (1)  yM1 = m sin t +   (1)  zM1 = nπ + nt − 

r1n sin t n2 + m2 r1n cos t n2 + m2 r1m

. (29)

n2 + m2

From Eqs. (4), (20), (21), (23), (25) and (28), the equation of the driven center curve is derived as Eq. (30):

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 ( 2)  xM 2       ( 2)  yM 2       2  zM( 2)     

  r2 m = ( m − a ) cos θ −  nπ + nt − b + n2 + m2   r2 n t +π t +π + ⋅ cos sin i12 i12 n2 + m2

   sin θ  ⋅  

  r2 m = − ( m − a ) cos θ −  nπ + nt − b + n2 + m2   r2 n t +π t +π cos ⋅ sin + i12 i12 n2 + m2  r2 m = − ( m − a ) sin θ −  nπ + nt − b + n2 + m2 

   sin θ  ⋅ (30)  

  cos θ 

Fig. 5. Simulation of the contact curves

Comparing Eqs. (21) and (29), it can be noticed that the driving center curve only has a relationship with the driving contact curve and the driving tine radius (r1); comparing Eqs. (26) and (30), the driven center curve only has a relationship with the driven contact curve and the driven tine radius (r2). That is to say, the driving and driven center curves are irrelevant from each other and either r1 or r2 can be selected according to their own demanding strength. 4 VIRTUAL SIMULATION The equations of the driving and driven contact curves are unique if and only if the following six parameters are given: m, n, a, b, θ and i12. During the virtual simulation, the same pair of contact curves as in the example are used. The six parameters are selected as below: m = 5 mm, n = 4 mm, a = 24 mm, b = 10 mm, θ = 120° and i12 = 3. Substituting the parameters into Eqs. (21) and (26), the equations of the driving and driven contact curves as Eqs. (31) and (32) are obtained. The virtual simulation is shown in Fig. 5.

 xM(1) = 5 cos t  (1) π   yM = 5 sin t  −π ≤ t ≤ −  , (31) 2   (1)  zM = 4π + 4t

 ( 2) 19  3 t +π ( 4π + 4t − 10 ) cos  xM =  − 2 3  2   19  3 t +π  ( 2) . (32) ( 4π + 4t − 10 ) sin  yM = −  − 3 2 2      z ( 2) = 19 3 + 1 ( 4π + 4t − 10 )  M 2 2 

638

Substituting the parameters into Eqs. (29) and (30), the equations of the driving and driven center curves as Eqs. (33) and (34) are obtained.  (1) 4r1 sin t  xM1 = 5 cos t − 2 4 + 52   (1) 4r1 cos t , (33)  yM1 = 5 sin t + 2 4 + 52   (1) 5r1  zM1 = 4π + 4t −  4 2 + 52

 ( 2)  xM 2       ( 2)  yM 2       2  zM( 2)     

19 5r2 3 = −  4π + 4t − 10 + 2 2 2 4 + 52   4r2 t +π t +π ⋅ cos + sin 2 2 3 3 4 +5

    

19 5r2 3 = − −  4π + 4t − 10 + 2 2  4 + 52  2 4r2 t +π t +π cos ⋅ sin + 2 2 3 3 4 +5 =

5r2 19 3 1  +  4π + 4t − 10 + 2 2 4 2 + 52

     . (34)

  

Once the values of r1 and r2 are determined, there are unique center curves corresponding with the contact curves. Therefore, the shape of the driving and driven tines can be simulated in Pro/E. In the industry, the radii of the tines are given according to the actual need. However, to testify to the irreverence of the driving and driven tines, both r1 and r2 with various values are chosen and matched as pairs. To avoid interference, the radii would be assured to be in a reasonable range, which can be easily guaranteed during the simulation.

Ding, J. –Chen, Y. –Lv, Y.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 633-641

Suppose the numbers of the driving and driven tines are z1 and z2, respectively. If z1 = 5, according to the definition of the transmission ratio, we derive that z2 = 15. As the numbers of the driving and driven tines are defined, then the shape of the SCMW is fixed, as shown in Fig. 6. a) r1 = 0.4 mm

r1 = 0.5 mm

r1 = 0.6 mm

Fig. 6. Simulation of the driving and driven wheels

The meshing of the SCMW is shown as in Fig. 7. The simulation results show that the tines always mesh at the same pair of contact curves and that the value of neither r1 nor r2 will affect the meshing.

b) r2 = 0.6 mm r2 = 0.7 mm r2 = 0.8 mm Fig. 8. SCMW samples; a) samples of driving wheels, b) samples of driven wheels

Fig. 9. Experimental schematic diagram Fig. 7. Simulation of the SCMW

5 KINEMATIC EXPERIMENT Using the data from the simulation above (also seen in Table 1), we manufacture some SCMW samples to do experiment to testify the irrelevance of the driving and driven wheels. The samples are produced through Selective Laser Melting (SLM) technology [11]. All the driving wheels have the same driving contact curves, as shown in Table 1, but different tine radii (r1), as shown in Fig. 8a; all the driven wheels have the same driven contact curves, as shown in Table 1, but different tine radii (r2), as shown in Fig.8 (b). Table 1. Uniform parameters of SCMW samples m 5 mm

n 4 mm

a 24 mm

b 10 mm

θ 120°

i12 3

z1 5

z2 15

The test rig made by our research group [1] to [3] is adopted to do the experiment. The experimental schematic diagram is shown in Fig. 9, and the test rig is shown in Fig. 10. Design of Space-Curve Meshing-Wheels with Unequal Tine Radii

Fig. 10. Test rig

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In the experiment, to keep the pair of contact curves constant and match the driving and the driven wheels with different tine radii each time, continuous records of contact tines at different locations are captured with high quality camera. For example, as shown in Fig. 11 are continuous records of the mesh between the driving tines with r1 = 0.5 mm and the driven tines with r2 = 0.8 mm. After recording the rotation speeds of the driving and the driven wheels for a while, the corresponding average ratios are calculated. As shown in Table 2, the data in the same column indicate the meshing between the same driving wheel and different driven wheels, while the data in the same row indicate the meshing between the driving wheels and the same driven wheel.

errors. It can be reduced by improving manufacturing technics and experiment conditions. It is noteworthy that the lengths of the tines do not affect the error in theory. However, as the tines are made through SLM technology, their manufacturing error accumulates as they become longer. During the experiment, the meshing of the driving and driven wheels with unequal radii in acceptable accuracy was accomplished. From similar continuous records like Fig. 11, it has been confirmed that the tines obtained always mesh at the same pair of contact curves, so the tine radii of the driving and driven wheels are irrelevant from each other. It can be concluded that the method presented is reliable.

Table 2. Average ratio of SCMW with the same pair of contact curves

In this paper, a new method based on the contact curves is proposed to design the SCMWs with unequal tine radii. It is illustrated with a design example in detail, and testified with both simulation and experiment. In comparison with existing design methods, the method presented has two obvious advantages as below: 1) The radii of the driving and driven tine do not affect the meshing process, and the radii of the driving and driven tines can be designed independently according to their working demands. 2) It is the theoretical foundation of the tine shape optimization based on the strength condition.

r1 [mm]

i12 r2 [mm]

0.6 0.7 0.8

0.4

0.5

0.6

2.98 3.02 3.01

3.00 2.99 3.00

3.01 2.98 3.02

From Table 2, the average transmission ratio measured is from 2.98 to 3.02, while the theoretical transmission ratio is 3. The maximum relative error is 0.6%. This relative error is the combined result of manufacturing errors, assembly errors and measure

6 CONCLUSION

Fig. 11. Continuous records of contact tines at different locations

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This method possesses several prospects to conduct further study. With this method, even the SCMW with variable radii and invariable stress can be designed. To identify the optimized radii, the relationship between the stresses and the radii is in progress. The shape selection rule would be established afterward. 7 ACKNOWLEDGMENT It is our pleasure to thank anonymous reviewers and editors for their valuable comments and suggestions. We thank the National Natural Science Foundation of China (No. 51175180) for the support of the research presented in this paper. 8 NOMENCLATURE r1 r2 φ1 φ2 ϖ1 ϖ2 ν1 ν2 ν12 i12 θ a b Mo1 M21 t β γ M M(1) M(2) M1 M2 uuuuur MM 1 uuuuur MM 2 m n p

Radius of driving tine Radius of driven tine Rotation angle of driving wheel Rotation angle of driven wheel Angular velocity of driving wheel Angular velocity of driven wheel Velocity of driving tine Velocity of driven tine Relative velocity Transmission ratio Included angle between angular velocity vectors Distance from point op to axis z Distance from point op to axis z Transformation matrix from o1 – x1 y1 z1 to o – x y z Transformation matrix from o1 – x1 y1 z1 to o2 – x2 y2 z2 Scope parameter of helix curve Unit normal vector of driving curve Unit binormal vector of driving curve Meshing point Point at driving contact curve Point at driven contact curve Point at driving center curve Point at driven center curve Contact vector from M to M1 Contact vector from M to M2 Helix radius of driving curve Pitch parameter of driving curve Pitch of driving curve

Number of driving tines z1 Number of driven tines z2 (superscript) Corresponding coordinate 9 REFERENCES [1] Chen, Y.Z., Xing, G.Q., Peng, X.F. (2007). The space curve mesh equation and its kinematics experiment. 12th IFToMM World Congress, Besançon. [2] Chen, Y.Z., Xiang X.Y., Luo, L. (2009). A corrected equation of space curve meshing. Mechanism and Machine Theory, vol. 44, no. 7, p. 1348-1359, DOI:10.1016/j.mechmachtheory.2008.11.001. [3] Chen, Y.Z., Chen, Z., Fu, X.Y. (2011). Design parameters for spatial helix gearing mechanism. Applied Mechanics and Materials, vol.121-126, p. 3215. [4] Litvin, F.L. (2008). Gear Geometry and Applied Theory. Shanghai Science and Technology Publishers, Shanghai. (in Chinese) [5] Bergseth, E. Björklund, S. (2010). Logarithmical crowning for spur gears. Strojniški vestnik - Journal of Mechanical Engineering, vol. 56, no. 4, p. 239-244. [6] Fetvaci, C. (2010). Generation simulation of involute spur gears machined by pinion-type shaper cutters. Strojniški vestnik - Journal of Mechanical Engineering, vol. 56, no. 10, p. 644-652. [7] Staniek, R. (2011). Shaping of face toothing in flat spiroid gears. Strojniški vestnik - Journal of Mechanical Engineering, vol. 57, no. 1, p. 47-54, DOI:10.5545/svjme.2010.093. [8] Puccio, F.D., Gabiccini, M., Guiggiani, M. (2006). Generation and curvature analysis of conjugate surfaces via a new approach. Mechanism and Machine Theory, vol. 41, no. 4, p. 382-404, DOI:10.1016/j. mechmachtheory.2005.07.008. [9] Chen, Y.Z., Luo, L., Hu, Q. (2009). The contact ratio of a space-curve meshing-wheel. Journal of Mechanical Design, vol. 131, no. 7, p. 074501, DOI:10.1115/1.3116343. [10] Chen, Y.Z., Hu, Q., Su, L. (2010). Design criterion for the space-curve meshing-wheel transmission mechanism based on the deformation of tines. Journal of Mechanical Design, vol. 132, no. 5, p. 054502, DOI:10.1115/1.4001535. [11] Chen, Y.Z., Sun, L.H, Wang, D., Yang, Y.Q., Ding, J. (2010). Investigation into the process of selective laser melting rapid prototyping manufacturing for spacecurve-meshing-wheel. Advanced Material Research, vol. 135, p. 122-127, DOI:10.4028/www.scientific.net/ AMR.135.122. [12] Chen, Y.Z., Chen, Z., Ding, J. (2011). Space Curve Mesh Driving Pair and Polyhedral Space Curve Mesh Transmission, PCT/CN2010/078294. [13] Li, G.Y. (2007). Spatial Geometry Modeling and Its Application in Engineering, Higher Education Press, Beijing. (in Chinese)

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Integration of Simulation and Lean Tools in Effective Production Systems – Case Study

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A. Ranko Božičković1 – Milan Radošević2,* – Ilija Ćosić2 – Mirko Soković3 – Aleksandar Rikalović2 1 University

of East Sarajevo, Faculty of Transport and Traffic Engineering, Bosnia and Herzegovina 2 University of Novi Sad, Faculty of Technical Sciences, Serbia 3 University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Production systems that are by their structure designed according to principles of group technology must, despite their perfection, rapidly adapt to changes in surroundings and engage in a battle with their market rivals. First of all, they must get closer to customers and suppliers, representing one of first principles of lean philosophy. It is one of the ways to successfully valorise comparative values with competition, despite its internal restructuring. This paper presents the influence of certain lean tools as well as application of statistical analyses, simulation and graphics tools for achieving greater effectiveness and efficiency of production systems. Application or integration of these tools enables shortening of the production cycle, reduces the degree of complexity of material flows, reduces the supplies and expenditure of energy resources while it creates an increased degree of functionality of the organisation, utilization of workspace etc. Combination of different tools presented in this paper can valorise new technological, organisational and informational achievements in production that will secure an even better position on the market for industrial systems. Keywords: lean, effective systems, group technology, simulation

0 INTRODUCTION There are many publications on adopting good practices that were introduced during the 90s and have been used since and which refer to directing the focus on consumer demand, material savings and expense elimination (Lean concept) [1] to [4], improvement of quality (Six Sigma, TQM) [5] to [8], product and process development [9],[10] and many others, which are all in accordance with regulations on ecological consciousness, large leading organisations have solidified their positions on a very competitive market [11]. Lean concept, although it originated after World War II in Japan, has undergone a significant worldwide application at the beginning of the fifties after a book “the Machine that Changed the World“ [1] by an MIT professor was published. Authors have presented a model that helped the Japanese car industry (Toyota) achieve incredible rebirth and take leadership position in production compared to the American car industry. The Japanese model was called Lean, explaining that lean concept provides a way to define factors that affect the creation of new values, control the activities (with tools and methods, for a more detailed description of lean tools and methods see [12] and [13]) that bring values in the best way possible without disrupting the process and enables for the process to be as efficient as possible. Lean means working more with less human effort, equipment, time and space and at the same time provide the product that will satisfy the needs of consumers [2]. Implementation of lean philosophy to production or service systems that do business in more and more 642

dynamic surroundings of today, require a detailed analysis of time characteristics of the system such as: production takt-time, lead time, delivery time and others. It is known today that one of the more significant problems facing the production industry is timely product or services delivery as a response to an increasing consumer demand, which represents one of the points leading the lean philosophy. In order to better respond to the abovementioned problem Arsovski et al. suggests integration of strategic and tactical decisions and enabling synchronisation and modification of production plans on the production level as soon as possible [14]. In order to introduce synchronisation of the process it is necessary to have a detailed insight into process flows and their overlap. Description and a detailed representation of flows within the production system can be presented by flow maps, i.e. VSM. The book “Learning to See” represents the first publication where Value Stream Mapping is described in detail. Authors have defined VSM with the following sentence: “Wherever there is a product for a customer, there is a value stream” [15]. Authors have also described the benefit gained by using VSM true case study [16]. It is well known that there are companies whose production or service systems are still designed according to the traditional approach and where changes are very difficult to introduce, primarily referring to the management and initiating the awareness about the needs to upgrade the system by using new approaches such as lean. In order to ease the access to new ideas it is not enough to draw up flows of the existing system, it also requires additional

*Corr. Author’s Address: University of Novi Sad, Faculty of Technical Sciences,Trg Dositeja Obradovica,21000 Novi Sad, Serbia; radosevic@uns.ac.rs

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tools that, when combined with VSM, could provide the data in earlier decision and planning phases. Therefore, a tool is needed that would enable the generation of necessary production resources and statistical performances in real time, i.e. a simulation [17]. There is no singular definition of simulation [18] and [19] but it can be observed as a virtual environment [20] or model where the current state of the system is possible due to factors defined as significant for improvement of the observed system to virtually display and predict the behaviour of the future state of the system. As output a real time simulation of the system with relevant data is obtained, tables and it presents a significant support for the management in making new decisions. According to Raigipol, simulation models represent a very good tool that can be applied in very complex systems without the need for any detail simplification in order to carry out the simulation [21], on significance and benefits gained by using simulations see [17], [19] and [22] to [25]. The information that the management can gather by applying the simulations enables a comparative analysis of the current and future state of the system, with all performances significant for making decisions concerning whether the system satisfies the initiation of changes; and database as such, represents a significant foundation before lean philosophy is implemented. 1 METHODOLOGY Application of the graphical (Sigma Flow VSM), simulation software (Simul8) and the statistical program (Minitab) was done in the industrial system for the production of flexible pipes. The system was, in an earlier period, set on the basis of group technology. Products of this industrial system were sorted into groups based on KS-IIS-08 classification system [26] and are produced in seven work units functioning as production units, depending on which group they belong to. Effective production system structure referring to a total number of work units,

technological systems and other characteristics is given in Table 1. After a global analysis: of the complexity of the material flows, the section of the load of technological systems and the importance to raise the effectiveness and efficiency in work processes work unit 3 (RJ-3) was chosen for analysis. Visualization of particulars of the current state of the RJ-3 and in the production system related to the process of supply, flows, supplies, unfinished production, the number of employees working in the work process, technological cycles, preparatory-finalizing time and work process rhythm are analysed in the graph of the state done with Sigma Flow VSM (Fig. 1) [27]. With the analysis of the graph, the main storages for raw materials, semi-products and finished products can be seen. Interpretational storages, which are used as queue points for work subjects for the next operation, control and dispatch of parts are also visible. The timeline at the bottom of the depicted graph has two components: a) Duration of the operational cycles (value – added time) is 43 minutes for operations conducted in the work unit, 1.5 minutes for surface protection and 2.5 minutes for the production of finished products; b) Non-productive time (non value added time) which is in total 240 hours: 109 for transport and waiting and 131 hours for preparation and finishing. The state of the work unit RJ-3, production system is based on the traditional MRP planning (material requirements planning), based on the employment of the capacity of machines and people. This includes the state of push production (material purchasing from suppliers), storing at the company, lathe processing, milling machine processing, drilling, surface protection and installation. In front of every work station there is an auxiliary storage for unfinished production (Storage WC1 to storage WC10) and a check point. The graph demonstrates the return and

Table 1. Structure of the effective production system No. 1 2 3 4 5

EPS characteristics Number of different items Number of technological systems – machines Number of identical technological systems in the work unit (RJ) Approach to shaping of the material flows Approach to shaping of the spatial structures

1 2 12 6 13 12 1 3 Group approach Item approach

3 17 10 3

Work unit No. 4 18 14 4

Integration of Simulation and Lean Tools in Effective Production Systems – Case Study

5 30 19 6

6 13 13 6

7 8 14 2

Total 104 85

643

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Fig. 1. Graph of the current state of the production system (continues)

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Fig. 1. Graph of the current state of production system (extension)

canceled material flows, large waiting lines in front of work centers, forbidden unfinished production and a longer waiting period for the delivery of products to the buyer.

17 different parts of products (P1, P2, …, P17), being produced on 10 different machines (WC1, WC2, …, WC10) are produced in RJ-3. The graphic depiction of the flow of material in RJ-3 is demonstrated in (Fig. 2). Based on these depictions

Fig. 2. Graphic depiction of flows in work unit 3 (RJ-3) Integration of Simulation and Lean Tools in Effective Production Systems – Case Study

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it can be concluded that the flow path for 6 to 8 and 14 to 17 does not comprise of progressive movement between neighboring machine pairs and that there are reverse and cross flows. Machine

1 2

10 1

1 1

6 Product groups

5 1

9 10

3 4

1 1

Fig. 3. Preview of the initial matrix for RJ-3

By creating material flows we have accessed the transferal of paths to the initial matrix “machine-part” that demonstrates the presence “1” or absence “0” of parts on the specific machine (Fig. 3). By using the data 0-1 two matrixes of Jaccard‘s similarity coefficient SC are generated – one for parts and one for machines (Fig. 4). SD =

aij ai + a j − aij

where number of parts present at i and j machine, number of parts present at i machine, and number of parts present at j machine.

0.111

0.200

0.182

0.200 1.166 0.200

0.111 0.250 0.111 0.333

0.250 0.111 0.333

0.100

5 6 7

0.111 0.200 0.111 0

0.165 0.250 0.250 0.100

0.111 0.200 .0111 0.111

0.200 0.182

0.333 0.333 .0111 0 0

0.100

0.111 0.192 0.214 0

0.091

0.111 0.300 0.417

0.111

0.300

0.400

0.100 0.214 0.091 0.417

0.400

0.182

Fig. 4. Jaccard’s matrix of the machine similarity coefficient

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By using the similarity matrixes in the statistical program MiniTab an analysis has been performed of the hierarchical grouping of the machines and products. Based on the results 5 departments have been formed in the raw material storage (queue P1, P10 WC1, etc.), (Figs. 5a and b), four groups of machines with auxiliary product storages, establishing product kanban cards. The final group of machines at the installation work unit supplies the time for the tact, meaning the necessary rhythm for the product delivery to a specific buyer. On the researched basis it is possible to perform a reconfiguration of the space structure of a work unit (layout). With the performed grouping the final appearance of the reconfigured layout of technological systems and flows in RJ-3 is achieved which is shown in Fig. 6 and it represents all parts as a single operating group and two groups of machines between which there are only four inter-group progressive flows. Based on the given graph and observed deficiencies we have approached the production of the graph of the future state (VSM) of the production system with progressive material flows, eliminated reverse and interrupted flows, kanban system, on buyer demand production- pull system, known as “lean production system”, (Fig. 7) [27]. 2 SIMULATION AND STATISTICAL ANALYSIS After applying the graphic software we move on to the simulation of the production system by using simulation software (Simul8). The simulation is used for predicting the future state of the system based on Figs. 1 and 7 where the graphic depictions of current and future state of the system are shown. The main elements of the model, measurement parameters in the simulation and the simulation of the given system case can be seen in paper [28]. After the simulation with the Simul8 software package, a factor 23 analysis was performed of the lean principle and tools (production system, TPM and SMED). The influence of the aforementioned factors was observed in relation to: 1. duration of the production cycles Tcp and 2. size of stock in the processes. Data on duration of the production cycle on every level is provided in Table 2. The data from the first measurement in both EPS (current and future) was compared to the measured sizes in the realistic production conditions. The data matched in the span of up to 10%. The remaining measurements were simulated in the given span for the purpose of statistical processing. Statistical processing allowed

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A.

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Fig. 5. Group analysis for; a) parts, and b) machines

Fig. 6. Reconfigured layout of the technological systems and flows RJ-3

the demonstration of dependence between observed factors. The spatial layout of the plan of the experiment is presented in Fig. 8a. The numbers next to the tops of the squares represent the mean duration of the production cycle for the given factor level. While the graphic depiction of the influence of the observed factors on the production cycle (Pareto diagram) is given in Fig. 8b. From Fig. 8b it is visible that factor “a” (production system) has the biggest influence. It is followed by factors “c” (SMED), “b” (TPM) and a combination of factors “ac”, “bc”, “ab” and “abc”. It can be determined that a triple interaction is not significant. ANOVA output from Minitab sums up the main effects for three factors into one measure, which can be visible in Table 3. The value of ’’P’’ in the table

is from 0 to 0.919. The factors that have a value closer to zero have higher influence significance on the production cycle. It is visible that the biggest effect is produced by factor “A”, i.e. production system, its layout and pull principle. The interaction between factors “production system × SMED” is the strongest and amounts to -1.62 i.e. it produces the effect of 3.25. Model results of T estimate the value of each factor and an interaction between them. T-test in the table reveals and ranks the importance of certain factors: production system, SMED and finally TPM. However, the future state will change the order of SMED and TPM because the tuning of tools has been perfected, so the duration cannot the shortened. All that remains is the perfecting of tools so that TPM system fails less (the equipment ages), and it will result in higher use of the equipment, bigger production and shorter

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Fig. 7. Graphic depiction of the future state of the production system

Tcp. The “F” value in the tables represents the Fisher criteria for significance evaluation. Residual value in relation to the order of data is shown in Fig. 9. The behavior of the main effects of factors (production system, SMED and TPM) in production cycle Tcp is presented in Fig. 10, and their interaction in Fig. 11. 648

From the figure it is clearly visible that by going towards the new layout and pull principle, towards ’’with’’, SMED and TPM, the duration of a production cycle is shortened. The regression equation of the behavior of the duration of the production cycle Tcp is:

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 642-652

depending on the observed factors can be determined. The spatial layout of the plot comprised of Tcp with two factors is presented in Figs. 12 to 14. Table 3. Determined effects and coefficients for Tcp (Table from MiniTab) Estimated Effects and Coefficients for Tcp (code units) Term Effect Coef SE Coef T P Constant 428.66 3.664 117.64 0.000 Production -119.05 -59.53 3.664 -16.34 0.000 system TPM -12.75 -6.37 3.664 -1.75 0.090 SMED -17.49 -8.75 3.664 -2.40 0.022 Production -2.25 -1.13 3.664 -0.31 0.760 system A×TPM Production system -3.25 -1.62 3.664 -0.45 0.659 A×SMED TPM×SMED -2.75 -1.38 3.664 -0.38 0.708 Production system 0.75 0.37 3.664 0.10 0.919 A×TPM×SMED

b) Fig. 8. a) Spatial layout of the plan of the experiment; b) Pareto diagram of the influence of factors on production cycle Table 2. A tabular presentation of Tcp in an effective production system Effective Production System - EPS

TPM without SMED without with 519

550 450 PUSH + 470 existing layout 500 -a, -b, -c (1) 390 400 410 Reconfigured EPS with PULL 360 principle 370 +a, -b, -c (a)

500.3

with SMED without with 499

480.3

510 480 490 460 500 480 450 470 430 520 510 490 -a, -b, -a, +b, -a, +b, +c (c) -c (b) +c (abc) 371.3 370 351.3 380 380 360 360 370 355 350 365 345 375 380 340 +a, -b, +a, +b, +a, +b, +c (ac) -c (ab) +c (abc)

Measurements

Fig. 9. Residual times Tcp

1 2 3 4 5 Code 1 2 3 4 5 Code

Tcp = 429 – 59.5 Production system – – 6.38 TPM – 8.75 SMED . (1)

The regression analysis of the influence of factors is given in Table 4 from where the behavior of Tcp

Fig. 10. The effects of main factors in the observation of the duration of Tcp production cycle

Identical 23 factor analysis has been performed for the behavior of the raw material stock, semiproduction and finished merchandise in storage. The final regression equation for stocks in the processes is:

Integration of Simulation and Lean Tools in Effective Production Systems – Case Study

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Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 642-652

STOCK = 294190 – 157840 Production System – – 9255 TPM – 10140 SMED . (2)

The second experiment analyzed the influence of the same factors on total stock and had shown the insignificant influence of factor “production tract’’ with pull principle. Inter-operational stock is lowered with this as well as other observed factors by about 3 times (from the average 472,000 to 156,648 pieces).

Fig. 11. Interaction of observed factors

Table 4. Regression analaysis of the influence Tcp (Table from MiniTab)

Fig. 12. Position of the plot Tcp - production system - SMED

Regression Analaysis: Tcp versus Production system; TPM; SMED The regression equation is Tcp = 429 – 59.5 Production system – 6.38 TPM – 8.75 SMED Predictor

Coef

SE Coef

Constant Production system

428.655

3.459

123.91

0.000

-59.525

3.459

-17.21

0.000

TPM

-6.375

3.459

-1.84

0.074

SMED

-8.745

3.459

-2.53

0.016

S = 21.8788;

R–Sq = 89.5%;

R–Sq (adj) = 88.6%

Analaysis of Variance

Fig. 13. Position of the plot Tcp - TPM - SMED

Source

Regression

146414

48805

101.96

0.000

Residual Error

17233

479

Total

163646

3 DISCUSSION The statistical part of the experiment has mainly been conducted on two primary performances: the duration of a production cycle Tcp and total production stock. The first analysis proved the effect of the following factors: EPS, SMED and TPM on the duration of the production cycle Tcp and it was discovered that the use of reconfigured EPS, can potentially diminish the production cycle up to 20% (from 519 to approximately 390 hours). The production cycle will continue to diminish if we were to continue using the listed methods, principles and tools of the lean concept. The focus must be turned to TPM being that the technological equipment in the mentioned case is obsolete. 650

Fig. 14. Position of the plot Tcp - TPM – SMED

It can be concluded that with the result analysis it has been determined that the reconfigured EPS that has taken into consideration lean tools regarding the shaping of the material flows and spatial structure and the “pull” principle, has produced a more significant effect in relation to the other two factors. In the observed EPS it has been demonstrated that the influence of TPM is lower in relation to SMED. However, further improvements need to be directed towards these two factors of the lean concept. They

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 642-652

are definitely important in future work, especially concerning TPM. Table 5. Display of achieved results with the use of lean concept Process No. measurement characteristics Duration of 1 production cycle Tcp [h] The stock level of 2 semi-production [pcs] The level of stock 3 in the input storage [pcs] The level of stock in finished 4 merchandise storage [pcs] The degree of space 5 use EPS Technological 6 development time Efficiency of 7 Tcpp/Tcpn Effectives – degree 8 of the flow of the order P = Tcp / ∑Tii The degree of 9 organization functionality F=1/P The No. of operator 10 in the work process 11

Passive times [h]

The consumption of hot water and electrical

Pre lean (level “-1”)

Post lean (level “+1”)

Improvements

519

390

Lowered by 1.33 times

12000

1648

Lowered by 7.2 times

100,000

50,000

Lowered by 2 times

270,000

60,000

Lowered by 4.5 times

Concentrate storages around work units

Increased by 1.2 times

45.49

45.49 1.62

Same Increased

519×60 / 45.49 = 684

390×60 / 45.49 = 514

Increased

0.0014

0.0019

Increased

Same

169.9

64.4

Lowered by 2.6 times

Lowered

This is not considered to be the end of perfection in such a shaped spatial structure of the work unit and an effective production system. The focus can be directed towards rising of the automated transport to the machines. In the end, it is important to stress that by using graphic tool Sigma Flow VSM, simulation tool Simul8 where the simulation has been performed in 10 replications and was based on an eight hour work day, five days a week and statistical 23 analysis with this experiment possible improvements to the system are presented, and total improvement results are shown in Table 5.

4 CONCLUSION This paper describes the development of the systematic methodology for the implementation of the lean concept in the industrial systems. An effective production system is one of the representatives of the concept of production systems where such material flows have been established that they can be compared to the production in the process industry. The main idea in this paper was conducted in two directions; the first was meant to help the critics to in such or similar situations, use new initiations for upgrading the efficiency by using lean concepts and to become competitors in the global market, and the second to show the increase of efficiency and effectiveness of EPS and to lower the stock and production cycle in relation to the time, up to the moment of observation. It is important to mention the limitations that showed themselves during the research and were characterized through non-accepting of changes by the employees, mostly due to fear of loosing their jobs. Although, the work itself showed that the efficiency was increased without the change in number of employees. Realization of the research through time period made employees and other critics to change their opinion in great measure as well as to accept the changes in a positive way. By developing procedures, steps and phases of implementation of the lean concepts in the mentioned area there are realistic chances for further research that will include the lean concept and the concept of an effective system into one integrated concept for molding the production system. 5 REFERENCES [1] Womack, J., Jones, D. (1990). Machine that change the world. Macmillan Publishing, New York. [2] Womack, J., Jones, D. (1996). Lean Thinking: Banish Waste and Create wealth in Your Corporation. Simon&Schuster, New York. [3] Taiichi, O. (1988). Toyota Production System: Beyond Large-Scale Production. Productivity Inc., Portland. [4] Shigeo, S., Dillon, A. (1989). A study of the Toyota production system from an industrial engineering viewpoint. Productivity Press, Portland. [5] Tennant, G. (2001). Six Sigma: SPC and TQM in Manufacturing and Services. Gower Publishing, Hampshire. [6] Pyzdek, T., Keller, P. (2009). The Six Sigma Handbook. McGraw-Hill Companies, Inc., New York. [7] George, S., Weimerskirch, A. (1998). Total Quality Management: Strategies and Techniques at Today’s Most Successful Companies. John Wiley and Sons Inc., Toronto.

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[8] Vujovic, A., Krivokapic, Z., Sokovic, M. (2011). Improvement of business processes performances trough establishment of the analogy: Quality management system – Human organism. Strojniški vestnik - Journal of Mechanical Engineering, vol. 57, no. 2, p. 151-161, DOI:10.5545/sv-jme.2009.177. [9] Kušar, J., Rihar, L., Duhovnik, J., Starbek, M. (2008). Project management of product development. Strojniški vestnik – Journal of Mechanical Engineering, vol. 54, no. 9, p. 588-606. [10] Žargi, U., Kušar, J., Berlec, T., Starbek, M., (2009). A company‘s readiness for concurrent product and process development. Strojniški vestnik – Journal of Mechanical Engineering, vol. 55, no. 7/8, p. 427-437. [11] Preiss, K., Patterson, R., Field, M. (2004). The future directions of industrial enterprises. Zandin, K. Maynard’s Industrial Engineering handbook. McGrawHill Companies, Inc., New York, p. 135-163. [12] Page, J. (2004). Implementing Lean Manufacturing Techniques, Hanser Gardner, Cinncinati. [13] Feld, W. (2000). Lean Manufacturing: Tools, Techniques, and How to Use Them, St. Lucie Press, Florida, DOI:10.1201/9781420025538. [14] Arsovski, S., Arsovski, Z., Mirovic, Z. (2009). The integration role of simulation in modern manufacturing planning and scheduling. Strojniški vestnik - Journal of Mechanical Engineering, vol. 55, no. 1, p. 33-44. [15] Rother, M., Shook, M. (1997). Learning to See – value stream mapping to create value and eliminate muda. Lean Enterprise Institute, Cambridge. [16] Radošević, M., Ćosić, I., Soković, M., Božičković, R. (2011). Visual stream mapping – Visualise before acting. XV International Scientific Conference on Industrial Systems, p.44-47. [17] Abdulmalek, F., Rajgopal, J. (2007). Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. International Journal of Production Economics, vol. 107, no. 1, p. 223-236, DOI:10.1016/j.ijpe.2006.09.009. [18] Law, A. (2006). Simulation Modeling and Analysis, 4th ed. McGraw-Hill, New York.

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[19] Chung, C. (2003). Simulation Modeling Handbook: A Practical Approach. CRC Press LLC, Florida, DOI:10.1201/9780203496466. [20] Rihar, L., Kušar, J., Duhovnik, J., Starbek, M. (2010). Teamwork as a precondition for simultaneous product realization. Concurrent engineering – research and applications, vol. 18, no. 4, p. 261-273. [21] Raigopal, J. (2004). Principles and applications of operationa research. Zandin, K. Maynard’s Industrial Engineering handbook. McGraw-Hill, New York. 1677-1694 [22] Detty, B., Yingling, C. (2000). Quantifying benefits of conversion to lean manufacturing with discrete event simulation: a case study. International Journal of Production Research, vol. 38, no. 2, p. 429-445, DOI:10.1080/002075400189509. [23] Fetvaci, C. (2010). Genereation simulation of involute spur Gear machined by pinion-type shaper Cutters. Strojniški vestnik - Journal of Mechanical Engineering, vol. 56, no. 10, p. 644-652. [24] Tan, Y., Takakuwa, S. (2011). Use of simulation in a factory for business continuity planning. International Journal of Simulation Modelling, vol. 10, no. 1, p. 1-48, DOI:10.2507/IJSIMM10(1)2.172. [25] Fandino Pita, N., Wang, Q. (2010). A simulation approach to facilitate manufacturing system design. International Journal of Simulation Modelling, vol. 9, no. 3, p. 113-168, DOI:10.2507/IJSIMM09(3)4.162. [26] Zelenović, D., Ćosić, I., Maksimović, R. (1998). IISE – approach in development of effective manufacturing systems – companies, group technology and cellular management. A state of the art synthesis of research & practice, Cluwer pres, New York. [27] Božičković, R. (2005). Lean concept in efective manufacturing systems. PhD Thesis, University of Novi Sad, Novi Sad. [28] Božičković, R., Ćosić, I., Božičković, Z., Radošević, M. (2011). An application of simulation and graphic tools in lean production. XV International Scientific Conference on Industrial Systems, p. 483-489.

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 653-664 DOI:10.5545/sv-jme.2011.183

Assembly/Disassembly Analysis and Modeling Techniques: A Review Iacob, R. – Popescu, D. – Mitrouchev, P. Robert Iacob1,* – Diana Popescu1 – Peter Mitrouchev2 1 University

“Politehnica” of Bucharest, Romania Laboratory, Grenoble, France

2 G-SCOP

Optimization and realistic virtual simulation of the Assembly and Disassembly (A/D) process are relevant research subjects, considering the significant role played by these operations in the initial stages of the product design, as well as in the fabrication, ergonomics, training, service or recycling stages. Literature reports many methods used for analysis and optimization and different simulation applications based on assembly connection concept or which use information referring to components mating. Moreover, virtual reality (VR) environments have significantly evolved towards the A/D simulation, highlighting new requirements for the preparation stages and their integration. All these simulations address different objectives: A/D sequencing, path planning, ergonomic analysis etc., and are complementary to each other. The main objective of the research presented in this paper is to propose new tools for enhancing the A/D simulation capabilities and to define a software development pipeline, as part of an on-going research effort aimed at creating a complex virtual assembly simulation platform. In order to do that, firstly a comparative review of the assembly modules available in A/D analysis software and simulation platforms, and the assembly modeling tools provided by commercial Computer-Aided Design (CAD) software is made. Different elements are investigated: mating conditions (geometric constraints) used for reciprocally placing components in an assembly, functions used for contacts generation, as well as clashes and interferences detection tools. Furthermore, the analysis focuses on determining what type of information related to components relative mobility is available in the existing software and how this is used. Starting from here, a first implementation of the platform, which has been developed to address some assembly analysis tasks, is presented for illustrating the concepts and assessing the feasibility of the approach. Keywords: assembly/disassembly, virtual reality, modeling tools, simulation

0 INTRODUCTION In today’s global context, two main directions are critical for the industry: product manufacturing cost reduction and environment protection – product recycling at its end-of-life. Since the late 80’s it has been established that the A/D process generally represents almost one third of the product cost [1]. Therefore, it is important to design proper plans for product assembly – manufacturing, and disassembly – recycling. Also, a realistic A/D process modeling can improve efficiency, reduce cost and increase the percentage of product recycling. In order to accomplish these issues, different simulations based on digital mock-ups of products are needed. Although analysis and modeling software, currently used at different stages of the Product Development Process (PDP), can offer solutions to some of the above mentioned needs, the development of a dedicated A/D integrated simulation platform is still a necessity [2]. To obtain an optimum A/D process, different methods, mentioned in literature, are applied: nondirectional blocking graph [3], assembly stability graph [4], disassembly wave method [5], conceptual scheme [6], psycho-clonal algorithm [7], and interference matrix [8]. Also, since the 90’s, several

complex software for assembly analysis [9] and [10], as well as simulation programs based on multiagent systems [11] or which use contact information between assembly components [12], were developed. More recently, Virtual Reality (VR) environments have significantly evolved towards A/D realistic simulation [13] to [21] highlighting new needs for A/D simulation preparation. All these simulations address different objectives (A/D sequencing, path planning, etc.), which are complementary, but not at all incorporated to each other. Moreover, they are barely included into the PDP, especially if the 3D shape models of components take part to A/D simulation. The relative mobility of components is a key element contributing to A/D simulations based on 3D component models. This mobility can be represented either exactly with translations, rotations and helices or approximated with infinitesimal translations only, and it can be also deduced from the relative positions of the components or strictly specified by the user. Focusing on simulations where contacts between components are of particular interest to characterize their relative mobility, prior works [10], [12], [22] and [23] have shown that models fit into the following classes: apart from finite translations, possible movements are all reduced to infinitesimal

*Corr. Author’s Address: University Politehnica of Bucharest, Faculty of Engineering and Management of Technological Systems, 313 Splaiul Independentei, Bucuresti 060042, Romania; robert.iacob@gmail.com

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translations or to translations and rotations only without helical ones. Translational, rotational and helical movements can be described, but the contacts between components are assumed to cover the whole functional surfaces (planes, cylinders, spheres etc.). In addition, the identification of the contacts between components is usually interactive only, hence making A/D simulations very tedious and strongly reducing their use in the PDP. Since the contact between components is at the basis of most of the A/D simulations requiring 3D component shapes, the contact identification is addressed here as the first step in the A/D simulation process. Indeed, the corresponding process establishes links between component shapes, contact models and component kinematics, which provides a basic set of meaningful information. We note that currently almost all mechanical products are conceived using one of the common CAD modelers [24] to [28]. Thereby, the available assembly modules of 3D CAD software and their specific approach to modeling assemblies have a strong influence on how products are designed. Moreover, for the real-time simulation environments, the data exchange CAD to VR is one of the most important issues currently faced by the virtual prototyping community. The previous characteristics constitute key elements of a complete simulation platform and offer the set of features used to analyze scientific contributions, thus highlighting some of the requirements for providing a more generic simulation environment and an improved integration of A/D simulation in the PDP. The paper is organized as follows. Section 1 reviews some of the existing assembly analysis software, while section 2 presents a survey on various assembly immersive simulation platforms. Considering the key elements needed for a simulation of an A/D process, section 3 reviews the assembly modeling tools from the main commercial CAD software. Then, section 4 defines the set of requirements for a virtual assembly simulation platform and presents the software development pipeline. Section 5 describes the first approach of the platform. Based on the model preparation phases, the main treatments contributing to the contact identification and an example for application are described. Finally, section 6 briefly presents the conclusions and future work. 654

1 ASSEMBLY ANALYSIS SOFTWARE A review of the scientific contributions showed that A/D analysis is addressed through a wide range of aspects where the objectives of an A/D simulation cover sequence planning, path planning, accessibility evaluation, operation time optimization etc. From a complementary point of view, for most A/D analysis approaches, 3D shapes and features of components and/or assemblies are key elements. For instance, path planning required for moving components into a complex environment strongly relies on 3D shapes. Depending on the simulation purpose, these shapes can be either a polyhedron or a B-Rep NURBS. Based on the parameters previously defined, a characteristic set of scientific contributions is evaluated to explicit how assembly analysis software can address a larger range of simulations and better fit into the PDP, i.e. initiating an A/D modeling process without the need of a specific shape model and technological data as input. At the beginning of the 90’s, Baldwin et al. [9] developed software for generating and evaluating assembly sequences.

Fig. 1. System structure of ASPEN

The application is based on a disassembly algorithm for generating sequences and provides visual aids during evaluation. as input it uses 3D models of components and, in order to generate all the assembly sequences, the user must first provide, interactively, a set of data: parts orientation, contacts, and interferences. It should be mentioned that the activities of generating precedence information, generating assembly sequences and editing sequences

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were integrated by the developed application for the first time. Later, a computer-aided Assembly Sequence Planning and Evaluation (ASPEN) system was developed by Kanai et al. [10], which automatically searches all the geometrically feasible sequences by decomposing solid models of a product and chooses an optimum sequence with the smallest operating time (Fig. 1). ASPEN assembly model is managed by the Parasolid modeler and requires additional information, like a list of contacts, to compute the list of valid sequences. Based on contact information, and in order to evaluate operation complexity, the application creates a simple mobility model. Another simulation application was proposed by Léon et al. [12]. Being operational with OPEN CASCADE, i.e. providing NURBS-based models, it offers the possibility to model some of the mobilities of elementary contacts, but the specification of contacts is interactive. Hence, preparing an A/D process is tedious or even not accessible when assemblies incorporate tens or hundreds or even thousands of components, as it is the case for complex industrial products. This application allows a designer, who has defined a mechanism, to analyze, in a semi-automatic way, its assemblability and to generate the list with all the valid sequences of an assembly. This list can be further filtrated by using technological data associated to the geometric description of components. Despite its strong points, this framework cannot generate all the possible solutions because not all the valid trajectories are modeled. Consequently, it is important to be able to fully identify and model the contacts between the components as automatically as possible. An integrated framework – called RAPID assembly system, has been developed by Zha et al. [11] for design, planning, analysis and simulation of assemblies. It is built upon Petri nets and uses multiagent systems. RAPID Assembly system consists of 6 major functional components: assembly design agent, planning agent, construction agent, evaluation agent, simulation agent, and meta system agent. Each agent may include several subagents or consist of several functional parts. The meta system agent is used for integration, coordination and control of other agents. The assembly design agent is used for assembly modeling and design by incorporating the functionbehavior-structure modeling techniques and featurebased modeling techniques in the base application structure.

The assembly editor, a subagent of the design agent, can accept imported CAD files of individual components and organize them into an assembly representation. Using feature recognition techniques, the assembly editor can differentiate connectors between parts and assembly features on individual parts. The developed multi-agent intelligent environment is mainly based on STEP file format and on two assembly representation models. From our point of view, both models are limited because the information about the contacts or about the mating conditions is imported. Furthermore, there is no method for describing or for representing the component mobility. A different approach is to analyze the problem of selective disassembly. A method proposed by Srinivasan et al. [5] called “wave propagation” analyzes the assembly from the selected component outwards, and orders the components for selective disassembly. The main conclusion of this evaluation is that current assembly analysis software address the problem of A/D process simulation by considering the 3D representations of the components independently of each other and considering the assembly step as requiring the addition of information related to geometric constraints, contacts and relative mobility of the components. Moreover, only a few approaches [12] initiate the use of technological data and tend to view a digital model as providing more information than a set of isolated components. We note that extensive analysis of the A/D process is possible in the early stage of the PDP, if two elements are available: the 3D models of products and the mobility data, all other necessary information can be further deduced from these. Another domain of the scientific contributions characterizes the assembly simulations according to their interaction with the user. These simulations can be fully automatic, i.e. after the user has specified the input parameters, the objective of the simulation is reached without any further interaction; interactive, i.e. the simulation objective is reached through successive steps where the user adds different parameters; or real time, i.e. the user continuously provides input according to the component configuration perceived. This last category reflects the assembly simulations where immersive environments based on VR techniques are the central element of a simulation approach. VR technology has evolved to a new level of sophistication during the last decade, now it combines

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several human – computer interfaces to provide various sensations: visual, auditory, haptic, which enables users to become immersed in a computergenerated platform [2]. These environments use a polyhedral type representation for the components. The underlying concept of real-time interaction between the virtual components and the user is fairly adapted to simulation configurations where the evaluation of a design configuration is rather qualitative and based on the perception of the user in comparison to automated processes where an algorithm makes decisions about a given component configuration. Many scientific contributions focus on A/D simulations in VR, addressing the product or some of its subsystems rather than an isolated component.

information is used to build a constraint database, which is then utilized in real-time while running the VADE program. The main core is the CAD-toVADE extraction module which is used to extract the assembly hierarchy, assembly constraints, and polygonal models of all components from ProEngineer. The method is interesting, but limited in use being compatible only with ProEngineer. The simulation application proposed by Liu et al. [19] performs assembly relationship identification, constraint solution and constrained motion guidance for interactive assembly in VR through a constrained behavior manager (CBM) (Fig. 4).

Fig. 2. Positioning a bolt in real factory Fig. 4. Architecture of CBM

Fig. 3. Positioning a bolt in VADE

Jayram et al. [17] have developed an immersive virtual assembly tool called VADE – Virtual Assembly Design Environment (Figs. 2 and 3), the first functional prototype being available in 1995. VADE includes many features like stereoscopic viewing, tracking, and user interaction, and it supports twohanded assembly. The VADE software has the ability of extracting the assembly information from the CAD model. This 656

Models, imported in IGES or SAT formats, contain only geometric information, hence a necessary step before virtual assembly is to define the assembly ports, which describe connection interfaces between components (Fig. 5). Indeed, the user must interactively specify these connection ports by selecting a collection of geometric entities and providing other relevant parameters. After this step, the CBM module recognizes the potential assembly features between assembly ports and it performs the recognition of geometric constraints between surfaces. Brunetti et al. [13] described an approach towards modeling and validation of mechanisms in the conceptual design phase applying virtual reality techniques and kinematics simulation. The developed system, called VCD (Virtual Conceptual Design), allows to interactively assemble mechanisms and to experience its behavior within the same process. It is based on OpenInventor & OpenGL and provides an event handler that links the tracking information with the VR application.

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The program contains a set of specialized modules which handle the boundary representation (B-Rep) of the model (ACIS kernel), the geometric constraints between topological entities (faces, edges) and the shapes (volumetric form features) that can be created or modified from the system. However, it can simulate only some of the lower kinematic pairs and none of the higher kinematic pairs.

Fig. 5. Connection ports; a) bolt port, b) nut port, c) pin port, d) hole port, e) bearing port, f) parallel key port, g) tenon port, h) dovetail port, i) Parallel slot port, j) groove port, k) dovetail slot port

Wang et al. [15] proposed a CAD-linked virtual assembly environment. The presented approach is a kind of external integration with a CAD system through automation interfaces. A novel hybrid virtual assembly model is developed to support this external integration. It works as a combinator that links the precisely represented design dataset in CAD models and the corresponding hierarchically structured virtual assembly dataset in the VR application. Using the hybrid virtual assembly model, a framework has been developed to embed and apply CAD assembly constraints on the virtual assembly structure. Constraint-based manipulation is thus implemented in the virtual assembly environment by integrating Autodesk Inventor through automation interfaces. The virtual assembly application is launched as a stand alone program that runs out-ofprocess to the Inventor, which runs in an invisible mode. The proposed software architecture has some strong points, but it is limited because of the direct link with a specific CAD system. In addition to the applications described above, the companies developing CAD programs and PLM platforms create basic modules for A/D field, directly integrated into the industrial environments. In a

report, Toledo [14] describes the approach of NIAR Virtual Reality Center (VRC) for VR simulation. The proposed application uses the PTC Division Reality module to build an immersive tool for A/D process simulation. Different aircraft scenarios are investigated in order to test the techniques proposed (Fig. 6).

Fig. 6. Virtual mechanism assembly

Fig. 7. Haptic assembly environment

VR applications may not only rely on visualization, but use also haptics to get closer to real configurations. In these simulations, collision detection algorithms are fundamental and they use polyhedral models with specific requirements in terms of triangle equilaterality and accuracy of body penetration. As a result, a VR application involving haptics incorporates not only a component shape for visualization, but also a shape for haptics. Lim et al. [18] developed a system to evaluate collisions detected between various parts. The most significant, yet classical, example is the insertion of a bolt into a hole.

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A similar but extended approach was proposed by Garbaya et al. [16] (Fig. 7). They performed separate tests to evaluate collision detection and the amount of clearance needed has been calculated. In order to reduce the effect of these approximations and to obtain a proper virtual simulation, a complete contact model is required, which shows the importance of model processing for haptic simulations.

Fig. 8. Haptic assembly application

Recently, Tching [20] has shown that there is a strong interest in the transition phase between the free mode of control and the assisted mode of control. This corresponds to the transition between dynamic/quasi – static and kinematic physics. To switch between these modes, one solution is to ensure the continuity of the object’s velocity between the time of collision deactivation and the time of constraint activation. The perception of this change must be transparent for the user and must ensure the continuity of its movement, forbidding efforts instabilities and incoherencies. In order to test the proposed method, a simple simulation software tool was developed (Fig. 8). For the haptic rendering, a Virtuose 6D haptic device from the Haption Company was used. These switches between modes are the first approach to obtain a more realistic simulation of A/D operations, where the component kinematic mobility become an additional parameter of the digital model involved in the A/D simulation and control. One interesting option to avoid the model import operation is to build a solid modeler in a VR environment. Zhong et al. [21] presented an efficient constraint-based methodology for intuitive and precise solid modeling in VR. It uses a constraint-based methodology for intuitive and precise solid modeling. A hierarchically structured and constraint based data model is developed to support solid modeling in the VR environment. A constraint reasoning engine is also 658

developed to automatically deduce allowable motions for precise constraint-based 3D manipulations. The program allows parts creation using feature primitives, and assemblies building using constraint data management. The proposed application is useful but limited because the parts can be created only using primitives and the mobility model is used purely for design rather than A/D purposes. The research concerning the immersive simulations in general, and in particular for A/D applications, is divided into two categories, depending if the haptic sensations are used or not. The use of haptic devices necessarily involves collision detection in real time and effort generation where collisions take place. The relation between constrained movement and collision detection is still an open field for research in order to provide realistic sensations for the A/D operations. When immersive simulations do not use haptic devices, the A/D simulations utilize kinematic constraints to generate realistic movements for the insertion/extraction phase of the components. The current review showed that two types of approaches for the constraints generation are implemented: the interactive specification – the user specifies these constraints, or the automatic generation of these constraints during the simulation, depending on the configuration of components. In both situations, difficulties related to the analysis of the constraints consistency exist. It is important to mention that the delicate relation between collision detection and generation of the kinematic constraints is generally not discussed in the presented papers. 2 MODELING TOOLS The synthesis of current research showed that an A/D simulation is subjected to different shape representations, i.e. B-Rep NURBS models or polyhedral representations needed for immersive simulations. Although there are some 3D models built with VR tools and used only for VR testing applications, most of the mechanical products are designed using a standard 3D CAD program. In this context, a review of the assembly modeling tools from the main 3D CAD programs is a necessary step in order to propose a set of operators for assembly process modeling. Five programs – which cover more than 50% of the mechanical CAD market [29], are investigated. These are: Solid Works (SW) and CATIA V5 (CV5) from Dassault Systèmes, Solid Edge (SE) and

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UniGraphics (UG) from Siemens and KeyCeator (KC) from Kubotek Software. The last has a different modeling philosophy and it will be discussed in the second part of this section. The 3D CAD software considers an assembly model as the result of correct spatial arrangements of components. In order to easily create such arrangements, the designer specifies a set of standard constraints like coincidence, parallel, perpendicular, tangent, concentric, distance or angle. These type of geometrical constraints are well known and include mates between flat and/or cylindrical surfaces, alignment and orientation constraints. Different combinations of constraints can produce the same result (spatial positioning of the components) and these constraints do not express directly the possible relative motion between components. Each analyzed program offers a set of tools for smart mating to reduce the time needed to define an assembly. For example, CV5 offers Quick Constraints option which places the first possible constraint between selected geometry: point, plane, line or circle. This first possible constraint is established from a priority list which can be set by the user. SE proposes Flash Fit workflow. This option reduces the steps required to position parts when compared to the traditional workflow. A CAD assembly generally has a single objective – the relative positioning of components, while the kinematic simulation has the objective of movements modeling. It should be noted that, in some cases, the position of surfaces of components from an assembly, already partially constrained, is not properly detected and thus it is not possible to define a complete set of constraints. This leads to the impossibility of defining real kinematic links. Generally, in this situation, the user should interactively provide a set of data – this step being a time consuming one. In addition to classical constraints, the reviewed programs include an additional set of complex mates. For example, in SW exists Mechanical Mates group which contains: cam, hinge, gear, screw, etc. SE proposes an extended group of mates with similar names and functionality. The advanced mates are deployed in order to model the contacts and to partially reproduce the real movements allowed: a hinge mate can describe a pin contact or a screw mate can describe a helical contact. This set of mates can also be used for constraining some complex surfaces. These types of constraints are useful, but their effectiveness is limited because they describe the mobility of a small set of contacts and thus it is

impossible to define a complete model. Moreover, it is important to mention that the constraint (mate) concept was developed as a partial solution to build assemblies from parts, but it requires various improvements.

Fig. 9. Coincidence interferences

Fig. 10. Standard interferences

The analyzed programs also contain some assembly analysis functions: interference detection, clearance verification, sensors etc. Interference detection can be used to determine the interference between components, to display the true volume of interference as a shaded volume or to distinguish between coincidence interferences (Fig. 9) and standard interferences (Fig. 10). It is a useful tool, but only for visualization purposes as it does not provide detailed information about the contact zone and the resulted data can not be further used. UG offers an interesting option – Isolate Interference, which displays only the components interference bodies and export this information as a XML report. One related function is clearance verification used to check the clearance between different components in assemblies (Fig. 11). The software checks the minimum distance between the components and reports clearances that fail to meet the minimum acceptable clearance specified. Sensors monitor the selected properties of parts and assemblies and alert the user when values deviate from the specified limits. Apart from the main assembly module, each reviewed CAD software proposes a set of wizards: Motion module – SW, DMU Kinematics – CV5, Motion Simulation – UG. These embedded

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applications offer conversion functions of geometric constraints in kinematic linkages, thereby reducing duplication, but only for some of the constraints – complex mates must be manually redefined before the analysis.

Fig. 11. Clearance verification

When assembly models are imported from a different CAD system, the constraints must be redefined in order to have a complete representation of the product model. Similarly, when an assembly model is exported to a kinematic analysis system, the kinematic links between the components must be specified. According to the analyses made in this section, all four programs are interesting and useful, but lack strong properties for the description of assemblies. Another conclusion is that these environments express the mobility between components only for an operational configuration of a product, but an A/D process requires the mobility model of all components and all trajectories between components, because all of them are related potential solutions for an A/D operation. Almost every CAD modeler includes functions for relative positioning of components and contains assembly modules which offer the possibility to define constraints between components. These constraints are limited to the specification of the relative position of surfaces, or axes related to each component, but not necessarily attached to the contact surfaces between components. This means that the contact surfaces – the functional surfaces involved in these constraints, are not explicitly identified and their locations are not really considered in the process of interference zone detection. Furthermore, the information about geometrical constraints is not used to define the relative mobility of the components and the proposed constraints are related to the position of components, but do not explicitly represent the contacts between components. 660

Therefore, this type of information is interesting but its effectiveness is limited and its transfer through data exchange standard formats is not currently possible. The positional constraints refer only to the reciprocal position of components and these data are neither sufficient nor consistent with the requirements for the identification of contacts, and these data are not intrinsic to the definition and characterization of the contacts and their commune zone associated. A different modeling philosophy is implemented in KC. This program represents an alternative to history-tree CAD software allowing users to edit solid model geometry without history trees or constraints. Being a non-parametric modeler, it has some strong points – especially for part design, and weaknesses – for assembly modeling. It earns equal praise for its ability to quickly create design concepts from scratch, to make changes to any part model in any format, and to extract and modify geometry in real-time on imported CAD models. The Direct Dimension editing technology allows parametric like changes to models without the burden of history or unwanted constraints (similar to synchronous technology developed by Siemens PLM – UG and SE). In order to model assemblies, this software generates a 3D representation of the product based on the use of a Common Reference Frame. Thus, all actors in the design of a product will generate the components in a defined position relative to the common reference frame, so there is no relative constraint position expressed between the components. This is a well known practice in automotive industry. As a result, the representation of the product is visually obtained and considered satisfactory when all components are simultaneously displayed in their place. Indeed, there is no information related to relations between components and the arrangement of the product is based solely on the users’ interpretation of the assembly scene. KC is a versatile application based on a new data technique, providing useful tools for the part design, but it lacks properties for the description and analysis of assemblies. KC specific modeling approach deploys precise 3D data editing, without the complexity of standard history-based parametric modeling tool, the models being built and edited regardless the model creation steps. These characteristics are the main difference from standard CAD software and can lead to a decrease in part design time. In addition to the above strong points, KC does not offer any information regarding the contacts between parts, interference zone or mobility data. Thus, it can

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be concluded that there is no true assembly module and no real product model. 3 SOFTWARE DEVELOPMENT PIPELINE The assessment of the state of the art in the previous sections showed that current analysis software, simulation platforms and CAD programs do not offer the necessary information and versatility required for a complete A/D process modeling and simulation. In this context, the main objective addressed in the present research is to define a software development pipeline for a virtual assembly simulation platform able to improve the A/D simulation process and to integrate it at various stages of the Product Life Cycle (PLC). The proposed A/D simulation platform is based on some new concepts and operators and it will have the following structure: import module, interface module, mobility module, sequence module, immersive module and export module. 3.1 Interface Concept The word interface describes a boundary across which two independent systems meet, act on or communicate with each other. In the proposed approach, the interface will designate a complete set of data about the mechanical contacts in a product model. Thus, it will contain information about: geometrical (mating) constraints, contact surfaces relative position, common area and information about the neighboring components. 3.2 Kinematical Combination Operator The proposed platform will be based on a kinematical combination operator able to describe all the families of trajectories associated to the interfaces or kinematic pairs from different components of a product. This operator will be used to model contact relations between elementary components of a product and to determine the relative mobilities of the assembly components. 3.3 Import Module & Data Representation Today, there are many CAD software and each mechanical design department uses one or more of them, depending on complexity of design. Moreover, different shape representations and model variants are produced by different CAD modelers even though they are quoted as standard format. Thus, a module

able to import 3D models from various mechanical design software products is the first requirement for the simulation platform. 3.4 Interface Module The main purpose of this research is to offer an intelligent tool to aid engineers in the design process, the proposed platform will offer a set of functionalities currently inexistent. Thus, an interface identification module will be able to automatically identify: the geometric constraints, the contact surfaces relative position, the common area, and to combine this information in a set of interfaces for a product. 3.5 Mobility Module The interface and joints information represent the input data for the mobility computing module. This one will calculate the mobility of a component from an assembly with respect to its surroundings. It will be based on the kinematical combination operator. For visualization purposes, a graphical representation of the valid trajectories will be implemented. 3.6 Sequence Module Having all the information related to the mobility data, the sequence module will be able to determine the sequence of mounting or dismounting of a component/entire product. This module will generate all the feasible sequences and it will identify the best one according to the criteria set by user. Another possible application of this module would be to store, on a device attached to the product, the optimal sequence of disassembly for the product or only for a valuable component in terms of recycling. This sequence will be read, in the recycling stage, by a disassembly system (robot), thus creating the frame for an automatic disassembly process. The solution is an extension of the idea proposed by Ostojic et al. [30]. 3.7 Immersive Module The immersive module, using the model data and the generated information, will offer a realistic simulation environment combined with haptic interaction. This module should contain the following features: • real-time simulation of A/D operations; • A/D sequence validation and editing; • two modes interaction: free mode and kinematic guided movement.

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3.8 Export Module The main objective of the proposed platform is the simulation of A/D operations in order to offer complete information about the A/D process. However, a very important aspect of any analysis and simulation program is the possibility to share information. Therefore, the platform proposed in this paper has to be able to collaborate with other software through an export module. This one will offer the possibility to export the models with semantic information attached for further use.

the maximal partitions over the boundary of each component (Fig. 12). Thus, partitions having the same semantic parameters are merged, e.g. adjacent cylinders having the same axis and radius, adjacent planes having the same position and normal etc.

4 SIMULATION FRAMEWORK Another aim of this work consists in introducing a subset of a simulation framework able to contribute to the A/D simulation process while reducing, as much as possible, the constraints of the input parameters [31]. For this, three data categories are considered as mandatory for A/D simulation: the component models, their relative positions and their functional surfaces. Generally, the input model comes from CAD software and it is important to take advantage of their B-Rep NURBS description to strengthen the algorithms and to obtain a more transparent access to the behaviors of the assembly components during A/D simulations. STEP was used as exchange format due to its robustness and efficiency in transferring component shapes, being interesting for noticing that these data are only geometric and are provided through the STEP files available with current CAD systems. There, all the information about functional surfaces is available in addition to B-Rep NURBS geometry, the contacts being related to the functional surfaces. The proposed simulation framework firstly automates the contact identification and it can identify seven types of contacts: Planar Fit (PLF), Cylindrical Joint (CLJ), Cylindrical Joint unidirectional (CJU), Spherical Fit (SPF), Linear Annular Fit (LAF), Helical Fit (HLF) and Undefined Type Contact (UTC). After this identification stage, a user’s interpretation is needed in order to meet the simulation hypotheses when components links cannot be fully inferred from the input geometry. The CAD modelers have some limitations due to the topological conditions. In order to have solids, each edge must be adjacent to two faces and the surface must be closed. For example, a closed cylindrical surface is decomposed into two surfaces. As a consequence, before starting the contact identification function, the C++ algorithm generates 662

a) b) Fig. 12. Example of maximal partitions generation; a) initial configuration, b) partitions obtained after merging operations

It should be noted that all the exported/imported CAD models have been created within some tolerance. In order to take these into account, the partition merging module uses two tolerances: a linear and an angular one. At the end of this operator, a List with the Merged Partitions (LMP) is added into the data structure for the contact identification process. This list is then used by the contact identification function. In the next step, for the selected assembly components, the application generates a List of Bodies (LBiB) intersecting each other. For this reason, the bounding box of each component is used in order to check the intersection between bodies and for speeding up the process. Then, using the LMP, created by the partition merging operator, four Lists with possible Contacts (LpC) are created for each type of surface. At this point, having all the necessary information structured, the contact identification is performed. For each type of contact – at the moment only seven types of contacts (above mentioned) are detected, the surfaces from the LpC, which belongs to the bodies from the LBiB, are tested and a corresponding list is created. The contacts identification process is fully automated, the list with all the contacts being obtained in only three steps: model tessellation, surface merging and contacts identification. Any complete assembly, previously designed using CAD software, can be virtually checked or analyzed very quickly using the proposed method/algorithm. In order to illustrate our approach, the assembly of a standard Tube Cutting Device (Fig. 13) has

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been selected. The device was chosen because it is a common and relevant example and because it contains a sufficient number of components: body – 1 piece; blade – 1 piece; lamella – 1 piece, spacer – 1 piece, pivot (lame axis) – 1 piece, washer – 1 piece, portroller R – 1 piece, port-roller L – 1 piece, axis – 2 pieces, roller – 2 pieces, catch – 1 piece, steering worm (endless screw) – 1 piece, button – 1 piece, screw M5 – 1 piece, screw M4 – 2 pieces (different length) and screw M3 – 2 pieces (same length).

available geometric and kinematic information and interference detection options.

Fig. 15. Partitions obtained after the merge operation

Fig. 13. Tube cutting device Fig. 16. List of contacts for the tube cutting device

Fig. 14. Initial configuration of the assembly

Based on the method described before three steps must be followed in order to generate the list with all the contacts of the product; Figs. 14 and 15 show the complete assembly imported in the preparation model framework. Using all these data, the list with all the contacts for the Tube Cutting Device assembly is created. The results: 24 – Cylindrical joints (CLJ) and 31 – Planar fits (PLF), are presented in the Fig. 16. 5 DISCUSSION In order to identify the main requirements and techniques for a complete virtual assembly simulation platform, the current paper presents a critical analysis of the existing assembly analysis software, as well as of the assembly immersive simulation platforms. Moreover, several commercial 3D CAD software used for assembly modeling are discussed in terms of

An additional purpose of the present research was to determine what type of information related to components relative mobility is currently available and how it is used in existing software. This analysis helped defining a coherent software development pipeline, providing a list of mandatory features to be included in the platform, as well as a set of input/output information for each described module. The group of proposed modules should form an innovative environment which will offer design engineers the necessary tools for optimizing the assembly modeling process and for providing useful information for the whole product lifecycle, from design and fabrication to recycling. Finally, the first implementation of the proposed platform is presented. It contains only a set of functions developed to prove the feasibility of the proposed concepts. Further research will address all the assembly tasks: analysis, simulation and recycling. 6 ACKNOWLEDGEMENTS This work was supported by CNCSIS-UEFISCSU, project number PN-II RU 233/2010, project title: “Assembly/Disassembly Process Modeling”, project type: “Research projects for stimulation of the founding/forming of young independent research teams”.

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7 REFERENCES [1] Boothroyd, G., Dewhurst, P. (1989). Product design for assembly. McGraw-Hill, New York. [2] Seth, A., Vance, J.M., Oliver, J.H. (2011). Virtual reality for assembly methods prototyping: a review. Virtual Reality Journal, vol. 15, no. 1, p. 5-20; DOI:10.1007/ s10055-009-0153-y. [3] Wilson, R.H., Latombe, J.C. (1994). Geometric reasoning about mechanical assembly. Journal of Artificial Intelligence, vol. 71, no. 2, p. 371-396, DOI:10.1016/0004-3702(94)90048-5. [4] Caracciolo, R., Ceresole, E. (1997). Forward assembly planning based on stability. Journal of Intelligent and Robotic Systems, vol. 19, no. 4, p. 411-436, DOI:10.1023/A:1007928631050.s [5] Srinivasan, H., Gadh, R. (2000). Efficient geometric disassembly of multiple components from an assembly using wave propagation. Journal of Mechanical Design, vol. 122, no. 2, p. 179-184, DOI:10.1115/1.533567. [6] Kopena, J., Regli, W.C. (2003). Extensible semantics for representing electromechanical assemblies. Conference ASME – IDETC/CIE, Chicago. [7] Prakash, A., Tiwari, M.K. (2005). Solving a disassembly line balancing problem with task failure using a psycho-clonal algorithm. Conference ASME – IDETC/CIE, Long Beach. [8] Tseng, H.E., Chang, C.C., Cheng, C.J. (2010). Disassembly-oriented assessment methodology for product modularity. International Journal of Production Research, vol. 48, no. 14, p. 4297-4320, DOI:10.1080/00207540902893433. [9] Baldwin, D., Abell, T.E., de Fazio, T., Whitney, T.E. (1991). An integrated computer aid for generating and evaluating assembly sequences for mechanical products. Transactions on Robotics and Automation, vol. 7, no. 1, p. 78-94, DOI:10.1109/70.68072. [10] Kanai, S., Takahashi, H., Makino, H. (1996). ASPEN: computer-aided assembly sequence planning and evaluation system based on predetermined time standard. Annals of CIRP, vol. 45, no. 1, p. 35-39, DOI:10.1016/S0007-8506(07)63012-1. [11] Zha, X.F., Li, L.L., Lim, Y.E. (2004). A multi-agent intelligent environment for Rapid Assembly Design, planning and simulation. Conference ASME – IDETC/ CIE, Salt Lake City. [12] Léon, J.C., Rejneri, N., Debarbouillé, G. (2001). Assembly/disassembly simulation early during a design process. Conference ASME – IDETC/CIE, Pittsburg. [13] Brunetti, G., Schneider, P., Stork, A. (2005). Constraintbased virtual conceptual design. Conference Virtual Concept, Biarritz. [14] Toledo, F.F. (2005). A full immersive assembly & disassembly simulation using PTC/division reality. NIAR Virtual Reality Center, Wichita. [15] Wang, Q.H., Li, J.R., Gong, H.Q. (2006). A CADlinked virtual assembly environment. International

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Journal of Production Research, vol. 44, no. 3, p. 467486, DOI:10.1080/00207540500319294. [16] Garbaya, S., Colado, U.Z. (2007). The affect of contact force sensations on user performance in virtual assembly tasks. Virtual Reality Journal, vol. 11, no. 4, p. 287-299, DOI:10.1007/s10055-007-0075-5. [17] Jayaram, S., Jayaram, U., Kim, Y.J., de Chenne, C., Lyons, K.W., Palmer, C., Mitsui, T. (2007). Industry case studies in the use of immersive virtual assembly. Virtual Reality Journal, vol. 11, no. 4, p. 217-228, DOI:10.1007/s10055-007-0070-x. [18] Lim, T., Ritchie, J.M., Dewar, R.G., Corney, J.R., Wilkinson, P., Calis, M., Desmulliez, M. (2007). Factors affecting user performance in haptic assembly. Virtual Reality Journal, vol. 11, no. 4, p. 241-252, DOI:10.1007/s10055-007-0072-8. [19] Liu, Z., Tan, J. (2007). Constrained behavior manipulation for interactive assembly in a virtual environment. International Journal of Advanced Manufacturing Technology, vol. 32, no.7-8, p. 797-810, DOI:10.1007/s00170-005-0382-5. [20] Tching, L., Dumont, G., Perret, J. (2010). Interactive simulation of CAD models assemblies using virtual constraint guidance. International Journal on Interactive Design and Manufacturing, vol. 4, no. 2, p. 95-102, DOI:10.1007/s12008-010-0091-7. [21] Zhong, Y., Shirinzadeh, B., Ma, W. (2005). Solid modeling in a virtual reality environment. The Visual Computer Journal, vol. 21, no. 1-2, p. 17-40, DOI:10.1007/s00371-004-0268-9. [22] Siddique, Z., Rosen, D.W. (1997). A virtual product prototyping approach to disassembly reasoning. Journal of Computer-Aided Design, vol. 29, no. 12, p. 847-860, DOI:10.1016/S0010-4485(97)00034-1. [23] Paczelt, I., Baksa, A., Szabo, T. (2007). Product design using a contact optimization technique. Strojniški vestnik – Journal of Mechanical Engineering, vol. 53, no. 7-8, p. 442-461. [24] 3DS Dassault Systèmes – Solid Works Documentation, (2009). [25] 3DS Dassault Systèmes – CATIA User manual, (2009). [26] Siemens PLM Software – Solid Edge User guide, (2010). [27] Siemens PLM Software – Unigraphics NX User manual, (2010). [28] Kubotek Software – KeyCreator Reference manual, (2008). [29] Jon Peddie Research – CAD Report 2010, from: http:// jonpeddie.com/cad_report, accessed on 2011-08-10. [30] Ostojic, G., Stankovski, S., Vukelic, D., Lazarevic, M., Hodolic, J., Tadic, B., Odri, S. (2011). Implementation of automatic identification technology in a process of fixture assembly/disassembly. Strojniški vestnik – Journal of Mechanical Engineering, vol. 57, no. 11, p. 819-825, DOI:10.5545/sv-jme.2010.131. [31] Iacob, R. (2010). Kinematic modeling of the component mobility for assembly and disassembly operations. PhD Thesis, Université de Grenoble, Grenoble.

Iacob, R. – Popescu, D. – Mitrouchev, P.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 665-672 DOI:10.5545/sv-jme.2012.681

Probabilistic Thermal and Electromagnetic Analyses of Subsea Solenoid Valves for Subsea Blowout Preventers

Cai, B. – Liu, Y. – Ren, C. – Abulimiti, A. – Tian, X. – Zhang, Y. Baoping Cai – Yonghong Liu* – Congkun Ren – Aibaibu Abulimiti – Xiaojie Tian – Yanzhen Zhang College of Mechanical and Electronic Engineering, China University of Petroleum, China A prototype of subsea solenoid valve for subsea blowout preventers is designed and manufactured. The deterministic and probabilistic thermal and electromagnetic finite element analyses are performed by using ANSYS software. The effects of uncertainties of five material properties, four physical dimensions and an applied voltage on the maximum temperature within the valve and the electromagnetic force with a given air gap are researched by means of Monte Carlo simulation (MCS) and response surface method (RSM). The thermal and electromagnetic experiments were done to validate the finite element analysis results. The results show that the radius of magnetic ring, applied voltage and thermal conductivity of 440C stainless steel have significant effects on the maximum temperature of subsea solenoid valve. The radius of plunger and inside radius of plunger sleeve have significant effects on the electromagnetic force of subsea solenoid valve. The results of finite element analysis and thermal and electromagnetic experiments indicate good matches. Therefore, the probabilistic finite element analysis shows its advantages in improving the development process and performance of subsea solenoid valves. Keywords: finite element methods, electromagnetic forces, electromagnetic heating, probability, valves, subsea solenoid valve

0 INTRODUCTION Subsea blowout preventers (BOP) play an extremely important role in providing safe working conditions for drilling activities in 3000 m ultra-deep water regions. Two redundant multiplex control pods, normally located on the lower marine riser package on the seafloor, are of crucial importance for the performance and reliability of BOP systems. The control pods contain 224 subsea solenoid valves immersed in low-temperature and high-pressure seawater [1]. As compared to shear seal valves, this valve provides about 70% savings in space reduction, which reduces the size and weight of subsea control systems greatly. Therefore, to maximize the electromagnetic force for a specific small volume valve, the main limiting quantity of maximum allowed temperature in seawater has to be considered [2]. The thermal and electromagnetic analyses for various electromagnetic devices have been performed by using the Finite Element Analysis (FEA) method. Tao et al. [3] developed an optimal design method for a high-speed response solenoid valve to achieve larger magnetic force and low power by using the FEA method. Moses et al. [4] studied the performance of a conventional electromagnetic actuator and a non-conventional electromagnetic device in order to demonstrate the advantages of the FEA technique in speeding up the design process and improving the performance of final products. Yatchev et al. [5] proposed a methodology to optimize a permanent magnet linear actuator with soft magnetic mover for electromagnetic valve. The flux density distribution, electromagnetic force and steady state temperature

distribution were researched by finite element analysis in order to verify the obtained optimal solution. Yang and Huang [6] designed a novel electromagnetic actuator which can produce three-dimensional forces for miniature magnetically levitated rotating machines via the FEA software. Angadi et al. [7] constructed a comprehensive multi-physics finite element model of a solenoid valve used in an automobile transmission to make predictions of the stresses, strains and temperatures within the solenoid valve. The results predict that the valve is susceptible to a coupled electrical-thermo-mechanical failure mechanism. Wu et al. [8] presented a design methodology of a normal stress electromagnetic linear actuator for fast tool servos during non-rotationally symmetric diamond turning based on analytical and finite element methods magnetic circuit analysis. The magnetic flux density and magnetic strength intensity of magnetorheological valve were also researched by using the FEA method [9] and [10]. Lipus et al. [24] presented model devices for magnetic water treatment, optimized for scale control at water capacities up to a few m3/h, using the computational program OPERA 15R1 with the FEA method. From these literatures, it can be seen that the FEA method has been widely used to study electromagnetic devices. However, these analyses are mainly deterministic. The reliability issues of electromagnetic devices have not been investigated using the FEA method. To address the growing need for stochastic and probabilistic finite element analysis, ANSYS Inc. released the ANSYS Probabilistic Design System (PDS). The PDS is an analysis technique for assessing the effect of uncertain input parameters

*Corr. Author’s Address: College of Mechanical and Electronic Engineering, China University of Petroleum, Dongying, Shandong 257061, China, liuyh@upc.edu.cn

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and assumptions on the model. This can account for the randomness in input variables such as material properties, boundary conditions, loads and geometry [11] and [12]. The PDS includes both the Monte Carlo Simulation (MCS) method as well as Response Surface Method (RSM). The PDS have been used to study the probabilistic problems for various structures. Nakamura and Fujii [13] demonstrated the probabilistic thermal analysis of an atmospheric re-entry vehicle structure and investigated the probabilistic temperature response by using MCS. Zulkifli et al. [14] evaluated the reliability or fatigue life of the solder joints in the ball grid array package by using RSM. Nemeth et al. [15] studied the effect of specimen dimension of single crystal SiC on the strength response by using PDS. Liu and Zheng [16] studied the strength reliability of composite laminated high pressure hydrogen storage vessel by using MCS and RSM. Cai et al. [17] and [18] investigated the buckling behaviours of filamentwound carbon fibre-epoxy composite pressure vessel with aluminium liner and composite long cylinders by using PDS. This work aims at studying the effects of uncertainties of material properties, physical dimensions and applied voltage on the thermal and electromagnetic issues by using the probabilistic FEA method. Five material properties, four physical dimensions and an applied voltage are taken as random input parameters, and the maximum temperature within the valve and the electromagnetic force with a given air gap are taken as random output responses. The thermal and electromagnetic experiments were performed to validate the finite element analysis results.

durability [21]. However, AISI 316L stainless steel is non-magnetic. Therefore, four components including plunger, spring pocket, plunger sleeve, and magnetic ring are used to form a magnetic circuit. They are made of AISI 440C martensitic stainless steel, which is strongly magnetic but has lower corrosion resistance to seawater than AISI 316L austenitic stainless steel [22]. All of the gaps within the valve, for example, the gap between the coil and the magnetic ring, are filled with conduction oil in order to transfer heat power and prevent high-pressure seawater from crushing the actuator. The coil conducts the current that provides magnetic flux, and it consists of numerous turns and layers of conducting copper wire, insulation and bonding material. The hydraulic fluid used in the subsea solenoid valve is water-glycol solutions, but not oil in order to reduce the pollution to ocean [23].

1 FINITE ELEMENT ANALYSIS

b) Fig. 1. a) schematic diagrams, and b) prototype of the subsea solenoid valve

1.1 Subsea Solenoid Valve The subsea solenoid valve is designed as a solenoid operated switching spring return actuator, which is mainly composed of a cover, a spring, a spring pocket, a coil, a coil bobbin, a plunger, a plunger sleeve, and a magnetic ring, as shown in Fig. 1. The plungertype structure is intended to produce small size [19] and [20]. When the coil is energized by DC voltage, the plunger of the valve retracts upward and extends downwards by releasing the stored energy from the spring. The cover of the actuator is made of AISI 316L austenitic stainless steel due to its high corrosion resistance to seawater, high strength, and high 666

1.2 Deterministic Analysis A thermal and electromagnetic model of the solenoid valve is developed in the finite element package ANSYS as shown in Fig. 2. Six materials including 316L stainless steel, 440C stainless steel, copper, Nylon, conduction oil and water-glycol solution are defined in the model. For the thermal analysis, the valve is described using 2-D thermal solid element PLANE55. The element is defined by four nodes with a single degree of freedom at each node. It can be used as a plane element or as an axisymmetric ring element with

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a 2-D thermal conduction capability. The model is meshed free, and the number of nodes and elements are 1670 and 3189, respectively. Free convection is assumed on the outer boundaries of the valve, expect on the line of symmetry, where axisymmetric boundary condition is assumed. Finally, the thermal analysis of the solenoid valve is performed to obtain the temperature distribution. For the electromagnetic analysis, 2-D coupledfield solid element PLANE 13 is used to describe the valve. The element is defined by four nodes with up to four degrees of freedom per node. It has a non-linear magnetic capability for modelling B-H curves or permanent magnet demagnetization curves. Similarly, the model is meshed free, and the number of nodes and elements are 1671 and 3182, respectively. The magnetic force boundary conditions are applied on the component of plunger, the uniform current density is applied on the elements of coil, and the flux parallel line conditions are applied on the all the outer boundaries. Finally, the magnetic flux line, magnetic flux density and electromagnetic force are predicted by performing the electromagnetic analysis.

temperature and maximum electromagnetic force for example. The PDS includes MCS and RSM. The MCS does not make any simplification or assumptions in the deterministic of probabilistic model, and the required number of simulations is not a function of the number of input variables, whereas this method requires plenty of computational time. The RSM replaces the true input-output relationship of MCS by an approximation function, and the evaluation of the response surface is much faster than a finite element solution. However, this method is unusable when true input-output relationship is not continuous [9].

Fig. 3. Physical dimensions of the subsea solenoid valve

Fig. 2. Finite element model of the subsea solenoid valve

1.3 Probabilistic Analysis The probabilistic finite element thermal and electromagnetic analyses of the subsea solenoid valve are performed by mean of ANSYS/PDS. The PDS is based on the ANSYS parametric design language, which allows users to parametrically build a finite element model, solve it, obtain results and extract characteristic results parameters such as the maximum

In this work, both of MCS and RSM are used to execute the probabilistic finite element thermal and electromagnetic analyses of the subsea solenoid valve. For the thermal analysis, the material properties including thermal conductivity of 316L stainless steel, 440C stainless steel and conduction oil, and convection heat transfer coefficient of seawater, physical dimensions including the radius of the plunger, inside and outside radiuses of plunger sleeve, and the radius of magnetic ring as shown in Fig. 3, and applied voltage are taken as random input parameters, and the maximum temperature within the valve is taken as random output response. For the electromagnetic analysis, the material properties including relative permeability of 440C stainless steel, physical dimensions as shown in Fig. 3 and applied voltage are taken as random input parameters, and the maximum electromagnetic force is taken as random output response. The statistical characteristics of material properties, physical dimensions and applied voltage are given in Table 1. The standard deviations

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Table 1. Statistical characteristic of material properties and dimensions Property k316 k440 koil hsea μ440 Rpl Rpsi Rpso Rmr U

Description Thermal conductivity of 316L stainless steel Thermal conductivity of 440C stainless steel Thermal conductivity of conduction oil Convection heat transfer coefficient of seawater Relative permeability of 440C stainless steel Radius of plunger (see Fig. 2) Inside radius of plunger sleeve (see Fig. 2) Outside radius of plunger sleeve (see Fig. 2) Radius of magnetic ring (see Fig. 2) Applied voltage

of variables are expressed as the product of mean valves and Coefficient of Variations (COV). For both of the probabilistic thermal and electromagnetic analyses, the Latin Hypercube Sampling was selected for MCS due to the fact that this technique avoids repeating samples that have been evaluated, and also forces the tails of a distribution to participate in the sampling process. The central composite design was used to locate the sampling points in the design space for RSM. 2 EXPERIMENTS In order to verify the finite element analysis results, the temperature within the subsea solenoid valve and electromagnetic force as a function of air gap were measured. Four resistance thermometer sensors (ZYWRNK-191, ZhongYiHuaShi, China) were fixed

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Unit W/(mK) W/(mK) W/(mK) W/(m2K) – m m m m V

Mean 15 24.2 0.111 200 10000 0.0063 0.0065 0.0080 0.0155 16

COV 0.06 0.06 0.02 0.01 0.05 0.004 0.003 0.003 0.002 0.010

Distribution Gauss Gauss Gauss Gauss Gauss Gauss Gauss Gauss Gauss Gauss

in Point A, B, C and D when the coil was wound and the valve was installed, as shown in Fig. 2. The steady state temperatures in the four points were measured when the solenoid was energized by applied DC voltage of 16 V in the constant temperature bath of 10 °C. A static experiment was performed to measure the relationship between the electromagnetic force and the air gap. The applied DC power was also supplied by a switching power supply (RXN-3020D), which is set to 16 V. The displacement of the plunger was determined by an eddy current displacement sensor (JX70-04-B-M16*1-75-03K), and the force was measure by an S-shape force sensor (PST-20). By recoding the voltage outputs of the force sensor and eddy current sensor, the relationship between the magnetic force and the air gap could be calculated.

b) c) Fig. 4. Distributions of a) temperature, b) magnetic flux line, and c) magnetic flux density Cai, B. – Liu, Y. – Ren, C. – Abulimiti, A. – Tian, X. – Zhang, Y.

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3 RESULTS AND DISCUSSION 3.1 Comparison of Analysis and Experimental Results The distributions of temperature, magnetic flux line and magnetic flux density predicted by using deterministic finite element analysis are shown in Fig. 4. As expected, the maximum temperature of 97.16 °C is found within the center of the coil, which is lower than the maximum allowed temperature of 120 °C. The minimum temperatures are located near the ends of the valve, which are for from the coil as shown in Fig. 4a. From Figs. 4b and c it can be seen that the main flux line is around the excited coil with a certain leakage. The predicted and experimental temperatures in Point A, B, C and D (see Fig. 2) are plotted as shown in Fig. 5. It can be seen that they have a similar trend except that the predicted temperatures are a littler higher than the experimental temperatures. The results verify that the ANSYS-based temperature calculation is correct.

force decreases rapidly. The experimental and predicted electromagnetic forces show a good agreement except that the experimental one is slightly higher than the predicted one. The results verify that the ANSYS-based electromagnetic force calculation is correct. 3.2 Probabilistic Thermal Analysis Results The distribution function histograms of maximum temperature obtained by means of MCS and RSM are shown in Fig. 7. It can be seen that for MCS, the sampling range of maximum temperature is between 84.97 and 104.42 °C, and the mean value and standard deviation are 95.90 and 2.94 °C, respectively. For RSM, the sampling range is between 83.89 and 104.97 °C. The mean value and standard deviation are 95.89 and 2.92 °C, respectively. The sampling range of the maximum temperature for RSM is bigger than that for MCS slightly due to that fact that RSM ran more Monte Carlo simulations. The mean maximum temperature for MCS and RSM are a little lower than the deterministic analysis results of 97.16 °C, whereas the error is very small.

Fig. 5. Predicted and experimental temperature of the subsea solenoid valve

Fig. 6. Predicted and experimental electromagnetic force of the subsea solenoid valve

The predicted and experimental electromagnetic force as a function of air gap is plotted as shown in Fig. 6. With the increase of air gap, the electromagnetic

Fig.7. Distribution function histogram of maximum temperature; a) MCS, and b) RSM

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Cumulative distribution function of maximum temperature with 95% confidence limit is shown in Fig. 8. The value of the cumulative distribution function at each point states the probability that the related parameter lays under the point. Therefore, when maximum temperature is 96 °C, the MCS and RSM almost have the same probability of failure of around 37%.

the radius of the plunger and convection heat transfer coefficient of seawater for MCS (Rmr> U > k440 > koil > k316 > Rpso > Rpsi > Rpl > hsea), whereas they are followed by thermal conductivity of 316L stainless steel, thermal conductivity of conduction oil, outside the radius of the plunger sleeve, convection heat transfer coefficient of seawater, inside the radius of the plunger sleeve and the radius of the plunger and for RSM (Rmr > U > k440 > koil > k316 > Rpso > hsea > Rpsi > Rpl). Although the orders of sensitivity for some random input variables are different, they have no significant influence on the maximum temperature, which can be ignored.

Fig. 8. Cumulative distribution function of maximum temperature; a) MCS, and b) RSM

The sensitivity of maximum temperature to random input variables for MCS and RSM is shown in Fig. 9. It can be seen that the radius of magnetic ring, applied voltage and thermal conductivity of 440C stainless steel have significant effects on the maximum temperature of subsea solenoid valve. The three variables are responsible for almost three quarters of the effect on the failure probability, with the other six variables together making up for the remaining one quarter. Therefore, more attention should be paid to the three variables when the valve is designed. The three variables are followed by thermal conductivity of 316L stainless steel, thermal conductivity of conduction oil, outside the radius of plunger sleeve, inside the radius of plunger sleeve, 670

Fig. 9. Sensitivity of maximum temperature to random input variables; a) MCS, and b) RSM

3.3 Probabilistic Electromagnetic Analysis Results The mean electromagnetic forces for MCS and RSM are 143.53 and 148.17 N, respectively, which are lower than the deterministic analysis results of 154.28 N. For the probabilistic electromagnetic analysis, only the sensitivity of electromagnetic force with the air gap of 0.25 mm to random input variables is given as shown in Fig. 10. It can be seen that the

Cai, B. – Liu, Y. – Ren, C. – Abulimiti, A. – Tian, X. – Zhang, Y.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 665-672

radius of plunger and inside radius of plunger sleeve have significant effects on the electromagnetic force of subsea solenoid valve. The two variables are responsible for three quarters or more of the effect on failure probability, with the other four variables together making up for the remaining part. Therefore, more attention should be paid to the radius of the plunger and inside radius of plunger sleeve when the valve is designed. The two variables are followed by applied voltage, the radius of magnetic ring, relative permeability of 440C stainless steel and outside radius of plunger sleeve (Rpl > Rpsi > U > Rmr > μ440 > Rpso), whereas they are followed by radius of magnetic ring, applied voltage, outside radius of plunger sleeve and relative permeability of 440C stainless steel (Rpl > Rpsi > Rmr > U > Rpso > μ440). Similarly, the orders of sensitivity for some unimportant random input variables are different.

solenoid valves for subsea blowout preventers are performed by using ANSYS software. The effects of uncertainties of five material properties, four physical dimensions and an applied voltage on the maximum temperature within the valve and the electromagnetic force with a given air gap are researched. A prototype of subsea solenoid valve was manufactured, and the thermal and electromagnetic experiments were done to validate the finite element analysis results. (1) The radius of the magnetic ring, applied voltage and thermal conductivity of 440C stainless steel have significant effects on the maximum temperature of subsea solenoid valve. (2) The radius of the plunger and inside radius of the plunger sleeve have significant effects on the electromagnetic force of subsea solenoid valve. (3) RSM and MCS predict different orders of sensitivity for some random input variables on maximum temperature and electromagnetic force; fortunately, they have small influences. (4) The results of the finite element analysis and thermal and electromagnetic experiments indicate good matches. The probabilistic finite element analysis (5) method shows the advantages in accelerating the development process and improving the performance of subsea solenoid valves. 5 ACKNOWLEDGEMENTS The authors wish to acknowledge the financial support of the National High-Technology Research and Development Program of China (No. 2007AA09A101), National Natural Science Foundation of China (No. 50874115), Program for Changjiang Scholars and Innovative Research Team in University (IRT1086), Taishan Scholar project of Shandong Province (TS20110823), Shandong Province Science and Technology Development Project (2011GHY11520) and Incubation Programme of Excellent Doctoral Dissertation of China University of Petroleum (No. 2010–02). 6 REFERENCES

Fig. 10. Sensitivity of electromagnetic force to random input variables; a) MCS, and b) RSM

4 CONCLUSIONS The deterministic and probabilistic thermal and electromagnetic finite element analyses of subsea

[1] Shaughnessy, J.M., Armagost, W.K. (1999). Problems of ultra-deepwater drilling. Proceedings of the IADC/ SPE Asia Pacific Drilling Technology Conference, APDT, Amsterdam, p. 179-–188. [2] Cai, B., Liu, Y., Tian, X., Wang, Z., Wang, F., Li, H., Ji, R. (2011). Optimization of submersible solenoid valves for subsea blowout preventers. IEEE Transactions on Magnetics, vol. 47, no. 2, p. 451-458, DOI:10.1109/ TMAG.2010.2100825.

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[3] Tao, G., Chen, H.Y., J, Y.Y., He, Z.B. (2002). Optimal design of the magnetic field of a high-speed response solenoid valve. Journal of Materials Processing Technology, vol. 129, no. 1-3, p. 555-558, DOI:10.1016/ S0924-0136(02)00633-7. [4] Moses, A., Al-Naemi, F., Hall, J. (2003). Designing and prototyping for production. Practical applications of electromagnetic modeling. Journal of Magnetism and Magnetic Materials, vol. 254-255, p. 228-233, DOI:10.1016/S0304-8853(02)00963-0. [5] Yatchev, I., Gueorgiev, V., Hinov, K. (2009). Optimization of an axisymmetric linear electromagnetic valve actuator. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 28, no. 5, p. 1249-1256, DOI:10.1108/03321640910969494. [6] Yang, S.M., Huang, C.L. (2009). Design of a new electromagnetic actuator which can produce threedimensional forces. IEEE Transactions on Magnetics, vol. 45, no. 10, p. 4153-4156, DOI:10.1109/ TMAG.2009.2022951. [7] Angadi, S.V., Jackson, R.L., Choe, S.Y., Flowers, G.T., Suhling, J.C., Chang, Y.K., Ham, J.K. (2009). Reliability and life study of hydraulic solenoid valve. Part 1 A multi-physics finite element model. Engineering Failure Analysis, vol. 16, no. 3, p. 874887, DOI:10.1016/j.engfailanal.2008.08.011. [8] Wu, D., Xie, X., Zhou, S. (2010). Design of a normal stress electromagnetic fast linear actuator. IEEE Transactions on Magnetics, vol. 46, no. 4, p. 10071014, DOI:10.1109/TMAG.2009.2036606. [9] Li, W.H., Du, H., Guo, N.Q. (2003). Finite element analysis and simulation evaluation of a magnetorheological valve. International Journal of Advanced Manufacturing Technology, vol. 21, vol. 6, p. 438-445. [10] Salloom, M.Y., Samad, Z. (2011). Finite element modeling and simulation of proposed design magnetorheological valve. International Journal of Advanced Manufacturing Technology, vol. 54, no. 5-8, p. 421429, DOI:10.1007/s00170-010-2963-1. [11] Reh, S., Beley, J.D., Mukherjee, S., Khor, E.H. (2006). Probabilistic finite element analysis using ANSYS. Structural Safety, vol. 28, no. 1-4, p. 17-43, DOI:10.1016/j.strusafe.2005.03.010. [12] Liu, D., Lai, X., Ni, J., Peng, L., Lan, S., Lin, Z. (2007). Robust design of assembly parameters on membrane electrode assembly pressure distribution. Journal of Power Sources, vol. 172, no. 2, p. 760-767, DOI:10.1016/j.jpowsour.2007.05.066. [13] Nakamura, T., Fujii, K. (2006). Probabilistic transient thermal analysis of an atmospheric reentry vehicle structure. Aerospace Science and Technology, vol. 10, no. 4, p. 346-354, DOI:10.1016/j.ast.2006.02.002. [14] Zulkifli, M.N., Famal, Z.A.Z., Quadir, G.A. (2011). Temperature cycling analysis for ball

672

grid array package using finite element analysis. Microelectronics International, vol. 28, no. 4, p. 1728, DOI:10.1108/13565361111097083. [15] Nemeth, N.N., Evans, L.J., Jadaan, O.M., Sharpe, W.N., Beheim, G.M., Trapp, M.A. (2007). Fabrication and probabilistic fracture strength prediction of high-aspect-ratio single crystal silicon carbide microspecimens with stress concentration. Thin Solid Films, vol. 515, no. 6, p. 3283-3290, DOI:10.1016/j. tsf.2006.01.041. [16] Liu, P.F., Zheng, J.Y. (2010). Strength reliability analysis of aluminium-carbon fiber/epoxy composite laminates. Journal of Loss Prevention in the Process Industries, vol. 23, no. 3, p. 421-427, DOI:10.1016/j. jlp.2010.02.002. [17] Cai, B., Liu, Y., Li, H., Liu, Z. (2011). Buckling analysis of composite long cylinders using probabilistic finite element method. Mechanika, vol. 17, no. 5, p. 467-473, DOI:10.5755/j01. mech.17.5.721. [18] Cai, B., Liu, Y., Liu, Z. Tian, X. Ji, R., Zhang, Y. (2012). Probabilistic analysis of composite pressure vessel for subsea blowout preventers. Engineering Failure Analysis, vol. 19, p. 97-108, DOI:10.1016/j. engfailanal.2011.09.009. [19] Chung, M., Gweon, D. (2003). Optimal design and development of electromagnetic linear actuator for mass flow controller. KSME International Journal, vol. 17, no. 1, p. 40-47. [20] Tsai, N., Chiang, C. (2010). Design and analysis of magnetically-drive actuator applied for linear compressor. Mechatronics, vol. 20, no. 5, p. 596-603, DOI:10.1016/j.mechatronics.2010.06.001. [21] Cai, B., Liu, Y., Tian, X., Wang, F., Li, H., Ji, R. (2010). An experimental study of crevice corrosion behaviour of 316L stainless steel in artificial seawater. Corrosion Science, vol. 52, no. 10, p. 3235-3242, DOI:10.1016/j.corsci.2010.05.040. [22] Tanaka, S., Ueda, K., Mitamura, N., Oohori, M. (2006). The development of an austenitic stainless steel bearing with high corrosion resistance. Journal of ASTM International, vol. 3, no. 9, JAI100424, DOI:10.1520/JAI100424. [23] Zheng, L., Neville, A., Gledhill, A., Johnston, D. (2009). An experimental study of the corrosion behavior of nickel tungsten carbide in some waterglycol hydraulic fluids for subsea applications. Journal of Materials Engineering and Performance, vol. 19, no. 1, p. 90-98, DOI:10.1007/s11665-0099416-8. [24] Lipus, L. C., Acko, B., Hamler, A. (2012). Magnetic device simulation modelling and optimisation for scale control. International Journal of Simulation Modelling, vol. 11, no. 3, p. 141-149, DOI:10.2507/ IJSIMM11(3)3.205.

Cai, B. – Liu, Y. – Ren, C. – Abulimiti, A. – Tian, X. – Zhang, Y.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 673-682 DOI:10.5545/sv-jme.2012.456

Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control Bajić, D, – Celent, L. – Jozić, S. Dražen Bajić* – Luka Celent – Sonja Jozić

University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Croatia Off-line process control improves process efficiency. This paper examines the influence of three cutting parameters on surface roughness, tool wear and cutting force components in face milling as part of the off-line process control. The experiments were carried out in order to define a model for process planning. Cutting speed, feed per tooth and depth of cut were taken as influential factors. Two modeling methodologies, namely regression analysis and neural networks have been applied to experimentally determined data. Results obtained by the models have been compared. Both models have a relative prediction error below 10%. The research has shown that when the training dataset is small neural network modeling methodologies are comparable with regression analysis methodology and can even offer better results, in which case an average relative error of 3.35%. Advantages of off-line process control which utilizes process models by using these two modeling methodologies are explained in theory. Keywords: off-line process control, surface roughness, cutting force, tool wear, regression analysis, radial basis function neural network

0 INTRODUCTION Process control is the manipulation of process variables motivated by process regulation and process optimization. The adaptation of process variables, therefore has the purpose of reduction of production cost or cycle time. Usually, this is done through adjusting three impact factors: the cutting speed, the feed and the depth of cut and employing parameter estimation to adapt the model to changing process conditions. Within this category, Furness et al. regulated the torque in drilling [1]. Process control can be performed as an on-line or off-line process. Off-line process control refers to preliminary definition of process variables as part of a process planning stage. Selection of variables is usually based on a machine book or the operator’s experience, therefore, computer aided process planning is a step forward and provides better results in production. Work carried out by Landers, Ulsoy and Furness concentrates on this subject [2]. Off-line process planning utilizes process models to select process variables based on experimental results like the influence of cutting parameters on surface roughness, tool wear and cutting force. The measured values are then used to determine the expected values according to an analytical model. Therefore, offline process control depends on the accuracy of the analytical model used. This is one of the drawbacks of this technique and an inability for error correction during the process. In this sophisticated technique the selection of modeling methodologies with their prediction errors has a great influence on the whole production. Lu [3] gives a detailed review

of methodologies and practice on the prediction of surface profile and roughness in machining processes. Different modeling methodologies have already been applied for solving the problems of prediction in face milling, like design of experiment (DOE) and regression analysis (RA) as well as neural networks. For example, Bajić and Belajić [4] and Oktem et al. [5] used response surface methodology, while Ezugwu, Arthur and Hines [6] as well as Benardos and Vosniakos [7] used back propagation neural network approach. Neural networks were also used for an intelligent prediction of milling strategies particularly in commercially available CAD/CAM systems [8]. Regarding tool wear estimation and tool breakage detection, Dong et al. [9] used the Bayesian multilayer perceptrons and Bayesian support vector machines for tool wear estimation, while Hsueh and Yang [10] used the support vector machines (SVM) methodology for tool breakage detection in modeling the face milling process precisely. Čuš and Župerl developed a system for monitoring tool condition in real time based on a neural decision system and Adaptive Neuro-Fuzzy Inference System (ANFIS) [11]. Parametric fuzzy membership functions based on neural network learning processes have been applied in the manufacturability assessment of free form machining [12]. Complex manufacturing and technological processes nowadays claim implementation of control systems using sophisticated mathematical and other methods for efficiency purposes. Thus, research is needed to get the mathematical approximations of machining processes and phenomena appearing as good as possible. In manufacturing engineers

*Corr. Author’s Address: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Ruđera Boškovića 32, 21000 Split, Croatia, dbajic@fesb.hr

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face two main practical problems. The first is to determine the values of the process parameters that will allow achievement of expected product quality and the second is to optimize manufacturing system performance with available resources. The decisions made by manufacturing engineers are based not only on their experience and expertise but also on the understanding of the machining principles and mathematical relations among influential parameters. The machining process is determined by the mutual relationship of the input values and its efficiency can be measured through output values. The great number of input values, as well as the fact that they have quantitative and qualitative nature contributes to the large expanse of possible interactions and their complexity. This model of the machining process was used in the research for this paper taking the parameters in italics and underlined among the input values as controlled ones and the same among the output values as measured ones (Fig. 1). The aim of this research is to find mathematical models that relate the surface roughness, tool wear and the cutting force components with three cutting parameters, the cutting speed (vc), the feed per tooth (f) and the depth of cut (ap), in face milling. In this research two different approaches have been used in order to get the mathematical models.

1 PROCESS PHENOMENA THAT EMBODY ANALYTICAL BASIS FOR MACHINING PROCESS PLANNING The objective of machining operations is to produce parts with specified quality as productively as possible. Many phenomena that are important to this objective occur in machining operations, like surface roughness, tool wear and cutting force. Modeling of these three process phenomena by manipulation of cutting parameters provides important information for machining process planning as a part of the off-line process control. Machining accuracy and capability of attaining the required surface quality is determined by selecting certain cutting parameters. Surface quality is one of the most specified customer requirements where a major indication of surface quality on the machined parts is surface roughness, Bernardos and Vosniakos provide a detailed review [14]. It is a widely used index of product quality and in most cases a technical requirement for mechanical products. Achieving the desired surface quality is of great importance for the functional behavior of a part. On the other hand, the process dependent nature of the surface roughness formation mechanism along with the numerous uncontrollable factors that influence pertinent phenomena, make it almost impossible to find a straightforward solution. Surface roughness is mainly the result of process parameters such as tool geometry and cutting conditions (feed per tooth, cutting speed, depth of cut), but in addition there is also a great number of factors influencing surface roughness (Fig. 2).

Fig. 1. Model of machining process

The first approach is a DOE together with an analysis of variance (ANOVA) and RA, and the second one is modeling by means of artificial neural networks (ANNs) [13] and [14]. In the past, the DOE approach was used to quantify the impact of various machining parameters on various output parameters, but nowadays ANNs has been proved as a method with great ability for mapping very complex and nonlinear systems. The milling process is an example of such a system and that justifies the usage of ANNs.

674

Fig. 2. Fishbone diagram with influential factors on machined surface roughness

Tool wear is a phenomenon that occurs on the contact area between the cutting tool, the workpiece and the chips [15]. Cutting tool wear is one of the key issues in all metal cutting processes, primarily

Bajić, D, – Celent, L. – Jozić, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 673-682

because of its detrimental effect on the surface integrity of the machined component, and also it has a major influence in machining economics causing possible anomalies in final workpiece dimensions or eventual tool failure. The monitoring of tool wear is an important requirement for realizing automated manufacturing. Therefore, information about the state of tool wear is important to plan tool changes in order to avoid economic loses. Tool wear is a very complex phenomenon (Fig. 3) presented by Yan et al. [16], which leads to machine down time, product rejects and can also cause problems to personnel although this has not yet been well clarified. In face milling, tool wear becomes an additional parameter affecting surface quality of finished parts.

Fig. 3. Fishbone diagram with the parameters that affect tool wear

the cutting forces are calculated according to the mean chip cross section in order to simplify the calculations. The researchers propose models that try to simulate the conditions during machining and establish cause and affect relationships between various factors that affect cutting force (Fig. 4) and the desired product characteristics. Cutting force is one of the important physical variables that provides relevant process information in machining. Such information can be used to assist in understanding critical machining attributes such as machinability, tool wear fracture, machine tool chatter, machining accuracy and surface finish. 2 DESIGN OF EXPERIMENT The planning of experiments means prior prediction of all influential factors and actions that will result from new knowledge utilizing the rational research. The experiments have been carried out using the factorial design of experiments. Milling is characterized by many factors, which directly or interconnectedly act on the course and outcome of an experiment. It is necessary to manage experiments with the statistical multifactor method due to the statistical character of a machining process. In this work, the design of experiments was achieved by the rotatable central composite design (RCCD). In the experimental research, modeling and adaptive control of multifactor processes the RCCD of experiments is very often used because it offers the possibility of optimization [18]. The RCCD models the response using the empirical second-order polynomial:

y = b0 + ∑ bi ⋅ X i + i =0

Fig. 4. Fishbone diagram with the parameters that affect cutting force

The surface formation mechanism during dynamic milling determines the cutting forces. The most regulated process variable in machining has been the cutting force, mainly for its reflection of process anomalies such as tool breakage and chatter [17]. In order to analyze the relation between the cutting forces and tool wear, cutting forces also need to be measured. The cutting forces developed during the milling operation are variable. Therefore, in practice

∑b

1≤ i < j

⋅ X i ⋅ X j + ∑ bii ⋅ X i2 , (1) i =1

where b0, bi, bij, bii are regression coefficients, and Xi, Xj are the coded values of input parameters. The required number of experimental points for RCCD is determined:

N = 2k + 2k + n0 = nk + nα + n0 , (2)

where k is the number of parameters, n0 is the repeated design number on the average level, and nα is the design number on central axes. RCCD of experiment demands a total of 20 observed conditions (experiments), 8 experiments (3 factors on two levels, 23), 6 experiments on the central axes and 6 experiments on the average level. The theory of the design of experiments and mathematicalstatistical analyses use coded values of input factors

Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control

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of the milling process. The coded values of three independent input factors have values on five levels, Table 1. Table 1. Physical and coded values of input factors

Physical values

Coded values

Levels X1 = vc [m/min] X2 = ap [mm] X3 = f [mm/tooth]

-1.682

-1

1.682

113.18

120

130

140

146.82

0.83

1.00

1.25

1.50

1.67

0.07

0.10

0.15

0.20

0.23

3 NEURAL NETWORK MODELING ANNs are non-linear mapping systems that consist of simple processors, called neurons, linked by weighted interconnections. Using a large amount of data out of which they build knowledge bases, ANNs establish the analytical model to solve the problems of prediction, decision-making and diagnosis. Fitting neural network parameters as a foreground learning task, allows the mapping of given input to known output values. The learning data set usually consists of input n-dimensional vectors x and corresponding output m-dimensional vectors y. Learning neural network parameters can be considered as a problem of approximation or interpolation of the hyper-plane through the given learning data. After the learning has finished, computation of responses of the neural network involves computation of values of the approximated hyper-plane for a given input vector. Approximation theory is employed with problem approximation or interpolation of the continuity of multi-variable function f(x) by means of approximate function F(w,x) with an exact determined number of parameters w, where w are real vectors:

x = [ x1 , x2 ,..., xn ] , w = [ w1 , w2 ,..., wn ] . T

To fulfill the approximation of the continual nonlinear multi-variable functions well enough, it is required to solve two key problems: 1. The proper selection of the approximate function F(w,x) that can efficiently approximate the given continuity of multivariable function f(x). This is known as the representation problem. 2. Defining an algorithm in order to compute optimal parameter w, according to optimal criteria given in advance. 676

Interpolation with a radial basis function (RBF) is one of the most successful methods for solving the problem of continuity multi-variable functions. With an implementation of the radial based function, the solution of the interpolation problem is given in the following form:

F ( x ) = ∑ ci ⋅ h ( x − xi ) , (3) i =1

where x n-dimensional input vectors, are regression coefficients, xi n-dimensional vectors of position of point of learning data set, ci unknown interpolation coefficient, h(.) radial basis function,║.║ Euclidean distance in multi-dimensional real space Rn, and N is the number of interpolation points. In the classical approach to RBF network implementation, the Gaussian function is preferred as a radial basis function. The researchers have shown that, in reality, where the learning data set is ordinarily weighted with some noise, better results have been achieved by approximation rather than interpolation. Namely, it is expected to filter the noise by means of approximation, in contrast to interpolation where the hyper-plane passes exactly through all points of the learning data set. It is a logical question whether it is necessary to compute the distance of all N points of the learning data set. Broomhead and Lowe [19] suggested selecting K points (called the center), where K < N. Now Eq. (3) has the form:

(

)

F ( x ) = ∑ c j ⋅ h x − t j , j =1

(4)

where ti n-dimensional vectors of the center of the radial basis function. With approximation, the number of center K is less than the number of points N. The number and the position of the centers of the neurons of the hidden layers has been determined in the learning procedure. Then, Euclidean distances of the input vector have been computed for the neurons of the hidden layer h (║xi-tj║), where is i = 1, ..., N (N is the index of the input vector), j = 1, …, K (K is the index of the neuron of the hidden layer). In this way, rectangular matrix (N×X) of the values of the hidden layer has been computed (H)ij=h(║xi-tj║). The implementation of N interpolation conditions leads to a predeterminated system of N linear equations with K unknown terms (weighted vector is c = [c1 c2 … cK]T). In this case, the optimal solution, according to the minimal square criterion, has been

Bajić, D, – Celent, L. – Jozić, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 673-682

achieved with a pseudo inversion of the matrix H. The solution represents the approximation of the multivariable function. The main advantages of the RBF model are its simplicity and the ease of implementation. The learning and generalization abilities of these networks are extremely good. The RBF model which is used in this study, for approximation of the two-variable function f(x), x = [x1 x2]T , is shown in Fig. 5. The construction of the radial basis function network involves three entirely different layers. The input layer is composed of three neurons. The output layer has one neuron. The number of neurons of the hidden layer is equal to the number of the K centers.

Setup 1 – relates cutting parameters and surface roughness, • Setup 2 – relates cutting parameters and tool wear, • Setup 3 – relates cutting parameters and Fx component of cutting force, • Setup 4 – relates cutting parameters and Fy component of cutting force, • Setup 5 – relates cutting parameters and Fz component of cutting force. Results of testing, in the form of regression analysis, for Setup 1 is shown in Fig. 6. R is a measure of agreement between the outputs and targets, and the aim is to get an R-value close or equal to 1. In the example in Fig. 6, it is 0.9547 and that indicates that the model is representative and with the same, 95.47% of deviations were interpreted. •

4 EXPERIMENTAL SETTINGS

Fig. 5. RBF neural network model

The type of machine tool used for the milling test was machining center VC 560 manufactured by Spinner. The test sample used in experiments was made of steel 42CrMo4 with dimensions 110×220×100 mm. The face milling experiments were executed by a tool CoroMill 390 with three TiN coated inserts, produced by Sandvik. Table 2. Measured experimental data

Fig. 6. Results of testing for generalization ability of Setup 3

The same network architecture has been used for modeling each of five physical relations separately. The network setups are named as:

Exp. Num. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Ra [μm] 0.59 0.53 1.45 1.18 0.61 0.70 1.55 1.19 0.73 0.50 0.48 1.82 0.85 0.92 0.84 0.79 0.85 0.81 0.86 0.87

VBmax [μm] 30 70 35 80 45 70 50 72 35 90 43 55 45 60 50 50 55 52 50 50

Fx [N] 196 157 290 235 192 198 316 261 205 185 160 308 166 250 190 188 190 192 189 187

Fy [N] 135 132 150 145 135 131 192 168 165 142 103 175 134 180 140 142 141 139 141 140

Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control

Fz [N] 36 40 48 51 36 38 56 46 45 39 33 54 40 45 41 42 42 43 42 40

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The cutting forces were measured by utilizing a Kistler dynamometer type 9271A. The dynamometer signals were then processed via charge amplifiers and an A/D converter to a computer. Tool wear and workpiece surface roughness were periodically measured, maximum flank wear land width VBmax of cutting tools by optical microscopy (10 times increase), and average surface roughness Ra of machined workpieces by a Surftest SJ-301, produced by Mitutoyo. The measurements of surface roughness were taken at five predetermined different places on the sample. During the process of measuring, the cut-off length was taken as 0.8 mm and the sampling length as 5.6 mm. Before the measurements were carried out all the measuring instruments were calibrated. All experiments were carried out without cooling and lubrication agents. Altogether 33 experiments were conducted. Twenty experiments were conducted in order to allow performance of ANOVA and regression analysis (Table 2), and an additional 13 experiments to obtain additional data for performing RBF modeling and verification of both models (Table 3). For those experiments, the values of the cutting parameters were randomly chosen within the range. Altogether, 28 data pairs have been chosen for the procedure of training and testing the RBF model. Five experiments were discarded because RCCD demands six repetitions at the center point. Before the training and testing, all input and output data have been scaled to be within the interval -0.9 and 0.9. After the training, models were tested for their generalization ability. Testing was performed with the data that had not been used in the training process. In order to conduct training and testing of the neural network models, a neural network toolbox embedded in MATLAB [20] was used. Eight data pairs, randomly selected and marked with an asterisk (*), were utilized for the validation of both RA and ANN modeling. 5 ANALYSIS OF RESULTS OF BOTH RA AND NEURAL NETWORKS SIMULATION The measured values of surface roughness, tool wear and cutting force components, obtained by 20 experiments are presented in Table 2. The ANOVA and RA have been performed using program package “Design Expert 6”. By applying regression analysis the coefficients of regression, multi-regression factors, standard false evaluation and the value of the t-test have been assessed. After omitting insignificant factors the mathematical models for surface roughness Ra, tool 678

wear VBmax and the components of cutting force Fx, Fy, Fz, were obtained as follows: Ra = −10.58 + 0.17 ⋅ vc + 14.25 ⋅ f − 6.04 ⋅10−4 ⋅ vc2 + +52.34 ⋅ f 2 − 0.16 ⋅ vc ⋅ f ,

(5)

VBmax = 0.65 − 7.2 ⋅10−3 ⋅ vc − 0.13 ⋅ f + 0.2 ⋅ a p + +4.24 ⋅10−5 ⋅ vc2 − 1.72 ⋅10−3 ⋅ vc ⋅ a p ,

(6)

Fx = 1526.9 − 15.7 ⋅ vc + 882.3 ⋅ f − 654.2 ⋅ a p + +7743.04 ⋅ f 2 + 162.6 ⋅ a 2p ,

(7)

Fy = 796.9 − 9.4 ⋅ vc + 357.7 ⋅ f − 144.9 ⋅ a p + +0.04 ⋅ vc2 + 86.9 ⋅ a 2p + 660 ⋅ f ⋅ a p ,

(8)

Fz = −63.81 + 379.5 ⋅ f − 3.25 ⋅ vc ⋅ f − 0.75 ⋅ vc ⋅ a p . (9) The squares of regression coefficient (r2) for Fx, Fy, Fz, Ra and VBmax are 0.9468, 0.9607, 0.9402, 0.9829 and 0.9908 respectively. Table 3. Additional measured experimental data Exp. Num. 21* 22 23* 24

Ra [μm] 0.79 0.86 0.82 1.71

VBmax [μm] 58 59 52 54

Fx [N] 176 193 200 250

Fy [N] 136 149 148 170

Fz [N] 42 45 45 51

25 26 27* 28* 29 30* 31* 32* 33*

0.60 1.34 1.55 0.64 1.61 1.46 0.71 0.65 1.60

53 64 55 41 55 64 61 40 57

165 270 206 182 221 195 191 197 251

142 185 143 135 146 149 134 143 171

40 58 48 41 56 45 41 42 52

Table 3 shows 13 additional measured experimental data. Data marked with an asterisk (*) were not used either in the network training or in the regression analysis. These data were utilized for the validation of both regression analysis and ANN modeling. Table 4 shows the values of surface roughness, tool wear and cutting force components obtained from both types of modeling, i.e. from the regression equations and from the simulation of neural network setups. Observing the changes of Ra and VBmax with increase of cutting speed, the connection between the two phenomena is established (Figs. 7 and 8). Therefore, cutting speed is closely related to

Bajić, D, – Celent, L. – Jozić, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 673-682

b) Fig. 7. Response surface for surface roughness as a function of cutting speed and feed per tooth obtained from RA (a) and RBF (b); for constant depth of cut of 1.25 mm

b) Fig. 8. Response surface for tool wear as a function of cutting speed and feed per tooth obtained from RA (a) and RBF (b); for constant depth of cut of 1.25 mm

b) Fig. 9. Response surface for Fx component of cutting force as a function of depth of cut and feed per tooth obtained from RA (a) and RBF (b); for constant cutting speed of 130 m/min

b) Fig. 10. Response surface for Fy component of cutting force as a function of depth of cut and feed per tooth obtained from RA (a) and RBF (b); for constant cutting speed of 130 m/min

emergence of built-up edge (BUE) and that implies its effect on machined surface roughness. By increasing the cutting speed the influence of BUE is reduced, and it also increases surface quality, but exaggeration

in the increase of cutting speed does not influence the further reduction of surface roughness because tool wear is simultaneously increased and it keeps roughness nearly constant. Feed per tooth is directly

Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control

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b) Fig. 11. Response surface for Fz component of cutting force as a function of depth of cut and feed per tooth obtained from RA (a) and RBF (b); for constant cutting speed of 130 m/min

proportional to surface roughness with a power of two, as well as cutting speed to flank wear. From the geometrical point of view, depth of cut has no direct influence on surface roughness because the height and form of roughness profile are independent of depth of cut. Its indirect influence is through the forming of BUE, chip deformation, cutting temperature, vibration etc. Depth of cut has also a minor effect on the tool wear, but sometimes in practice it is inversely proportional to the tool wear, i.e. by decreasing the depth of cut the tool wear increases. This is explained using the theory of dislocations. Namely, in smaller volume of material, there are smaller numbers of errors in its crystal lattice, causing the material is homogeneous, and thus difficult to machine.

Table 5. Testing the models capability for prediction of surface roughness, tool wear and cutting force Exp. Numb.

Relative error using regression [%] Ra [μm]

VBmax [μm]

Fx [N]

Fy [N]

Fz [N]

16.46

2.07

4.80

3.52

6.25

5.95

5.00

3.25

3.01

9.39

8.18

11.82

0.56

0.81

8.40 7.50

5.78

9.76

2.05

0.05

10*

10.68

5.00

4.26

5.53

7.71

11*

2.99

0.16

0.17

4.62

10.88

12*

6.15

9.50

8.55

4.76

9.67

13*

16.43

10.35

3.58

3.51

8.69

Average

9.08

6.71

3.40

3.23

8.56

Total average relative error: 6.19%

Table 4. Values obtained by regression analysis and neural network models Exp. Num.

Regression

Exp. Numb.

Relative error using neural network (%) Ra [μm]

VBmax [μm]

Fx [N]

Fy [N]

Fz [N]

VBmax [μm] 59.2 54.6 48.5

Fx [N] 167.5 193.5 204.8

Fy [N] 131.2 143.5 141.8

Fz [N] 39.4 40.8 43.9

3.49

0.17

6.50

1,39

0.12

21* 23* 27*

Ra [μm] 0.66 0.79 1.01

8.61

6.35

0.26

0.36

3.65

6.52

1.45

2.66

0.06

5.94

1.16

8.78

0.57

2.05

2.81

28*

0.62

37.0

178.3

135.1

37.9

10*

20.15

1.56

4.85

1.08

0.28

41.1 36.4 37.9 47.5

11*

3.79

4.10

0.16

1.29

6.37

12*

2.23

8.75

6.99

3.28

4.81

13*

7.19

0.53

0.47

5.25

1.71

Average

6.64

3.96

2.81

1.84

3.21

30* 31* 32* 33* Exp. Num. 21* 23* 27* 28* 30* 31* 32* 33*

680

1.43 0.65 0.61 1.17

67.2 61.1 36.2 51.1

186.7 191.3 180.2 242.1

140.8 127.8 136.2 165.1

Neural network Ra [μm] 0.82 0.91 1.03 0.67 1.03 0.70 0.66 1.30

VBmax [μm] 57.9 55.3 54.2 44.6 63.0 63.5 43.5 56.7

Fx [N] 187.4 200.5 200.5 180.9 204.4 190.7 183.2 252.2

Fy [N] 137.9 148.5 142.9 137.8 147.4 132.3 138.3 179.9

Fz [N] 42.1 43.4 45.5 39.8 44.4 38.2 39.9 51.1

Total average relative error: 3.35%

Figs. 9 to 11 show the results obtained from both models in the form of graphical representation for the x, y, z components of cutting force and its dependence on depth of cut and feed per tooth. Cutting speed has been kept constant at 130 m/min. It can be seen that the RA method predicts that the cutting force components depend almost linearly on both, depth of cut and feed per tooth. In graphical representations

Bajić, D, – Celent, L. – Jozić, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 673-682

of the RBF method nonlinearity can be seen, which better describes the real state of the milling process. The minimum values of cutting force components are achieved when feed per tooth and depth of cut nearly reach their minimum values. Increasing the cutting speed increases the angle of inclination of the plane shear layer separated materials, and reduces the length of the shear plane at constant shear strength. The force required for deformation of the material is then reduced. At low cutting speeds, the coefficient of friction increases, which is another reason for increased force. On the size of the cutting force, at the beginning of the process only the processing parameters are affected. During machining, cutting tool changes its properties because of tool wear. The cutting force at any point is equal to the initial cutting force plus the increment of the cutting force. This increment is different for different machining parameters. In order to test which modeling method gives a better prediction, a relative error of deviations from measured values has been calculated. Validation of both models was performed with the testing data set that had not been used in the training process. Relative errors obtained using RA and RBF methodologies have been compared, and the results of testing are presented in Table 5. The results from Table 5 indicate that the RBF model offers the best prediction capability with total average relative error of 3.35%. 6 CONCLUSIONS The purpose of this study is the research of possibility of surface roughness, tool wear and cutting force component modeling to collect the information needed for effective machining planning as part of off-line process control. The influences of the cutting speed, the feed per tooth and the depth of cut on surface roughness, tool wear and cutting forces in the face milling process have been examined in the study, and in order to model dependency between those parameters, regression analysis and neural network methodology were used. Regarding the results, both methodologies are found to be capable of accurate predictions of the surface roughness, tool wear and cutting force components, although neural network models give somewhat better predictions, with approximate relative error of 3.35%. The research has shown that when the training data set is relatively small (as in the study) neural network models are comparable with the RA methodology and can also offer even better results. More accurate predictions

ultimately improve off-line process control resulting in significant reduction of machining cost. Nevertheless, despite years of research and a multitude of success stories in the laboratory, only a small amount of modern technology has been transferred to production. Therefore, off-line process control as an approach that demonstrates its capabilities to be applied in practice and easily integrated in existing conditions still represents the key for successful machining and also the bridge between machining research and the production. 7 REFERENCES [1] Furness, R.J., Ulsoy, A.G., Wu, C.L. (1996). Feed, speed, and torque controllers for drilling. ASME Journal for Manufacturing Scientists and Engineers, vol. 118, p. 2–9. [2] Landers, R.G., Usloy, A.G., Furness, R.J. (2002). Process monitoring and control of machining operations. Mechanical Systems Design Handbook. CRC Press LLC, p. 85-119. [3] Lu, C. (2008). Study on prediction of surface quality in machining process. Journal of Materials Processing Technology, vol. 205, no. 1-3, p. 439-450, DOI:10.1016/j.jmatprotec.2007.11.270. [4] Bajić, D., Belaić, A. (2006). Mathematical modelling of surface roughness in milling process. Proceedings of the 1st International Scientific Conference on Production Engineering (ISC), p. 109-115. [5] Oktem, H., Erzurumlu, T., Kurtaran, H. (2005). Application of response surface methodology in the optimization of cutting conditions for surface roughness. Journal of Materials Processing Technology, vol. 170, p. 11-16, DOI:10.1016/j.jmatprotec.2005.04.096. [6] Ezugvu, E.O., Arthur, S.J., Hines E.L. (1995). Tool-wear prediction using artificial neural networks. Journal of Materials Processing Technology, vol. 49, no. 3-4, p. 255-264, DOI:10.1016/0924-0136(94)01351-Z. [7] Benardos, P.G., Vosniakos, G.C. (2002). Prediction of surface roughness in CNC face milling using neural networks and Taguchi’s design of experiments. Robotics and Computer-Integrated Manufacturing, vol. 18, no.5, p. 343-354, DOI:10.1016/S0736-5845(02)00005-4. [8] Klančnik, S., Balič, J., Čuš, F. (2010) Intelligent prediction of milling strategy using neural networks. Control and Cybernetics, vol. 39, no. 1, p. 9-22. [9] Dong, J., Subrahmanyam, K.V.R., Wong, Y.S., Hong, G.S., Mohanty, A.R. (2006). Bayesian-inferencebased neural networks for tool wear estimation. The International Journal of Advanced Manufacturing Technology, vol. 30, no. 9-10, p. 797-807, DOI:10.1007/ s00170-005-0124-8. [10] Hsueh, Y.W., Yang, C.Y. (2009). Tool breakage diagnosis in face milling by support vector machine. Journal of Materials Processing Technology,,

Modeling of the Influence of Cutting Parameters on the Surface Roughness, Tool Wear and Cutting Force in Face Milling in Off-Line Process Control

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vol.209, no. 1, p. 145-152, DOI:10.1016/j. jmatprotec.2008.01.033. [11] Čuš, F., Župerl, U. (2011). Real-time cutting tool condition monitoring in milling. Strojniški vestnik – Journal of Mechanical Engineering, vol. 57, no. 2, p. 142-150, DOI:10.5545/sv-jme.2010.079. [12] Korošec, M., Balič, J., Kopač, J. (2005). Neural network based manufacturability evaluation of free form machining. International Journal of Machine Tools & Manufacture, vol. 45, no. 1, p. 13-20, DOI:10.1016/j.ijmachtools.2004.06.022. [13] Özel, T., Karpat, Y. (2005). Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks. International Journal of Machine Tools & Manufacture, vol.45, no.4-5, p. 467-479, DOI:10.1016/j.ijmachtools.2004.09.007. [14] Benardos, P.G., Vosniakos, G.C. (2003). Prediction surface roughness in machining: a review. International Journal of Machine Tools & Manufacture, vol. 43, no. 8, p. 833-844. DOI:10.1016/S0890-6955(03)00059-2.

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[15] Roy, S.S. (2010). Modelling of tool life, torque and thrust force in drilling: a neuro-fuzzy approach. International Journal of Simulation Modelling, vol. 9, no. 2, p. 74-85, DOI: 10.2507/IJSIMM09(2)2.149. [16] Yan, J., Murakami, Y., Davim, J.P. (2009). Tool Design, Tool Wear and Tool Life. Cheng, K. (ed.) Machining Dynamics: Fundamentals, Application and Practice, Springer, London, p. 133-138. [17] Chaari, R., Abdennadher, M., Louati, J., Haddar, M. (2011). Modelling of the 3D machining geometric defects accounting for workpiece vibratory behaviour. International Journal of Simulation Modelling, vol. 10, no.2, p. 66-67, DOI: 10.2507/IJSIMM10(2)2.173. [18] Montgomery, D.C. (2001). Design and analysis of experiments, John Wiley & Sons, New York. [19] Novaković, B., Majetić, D., Široki, M. (1998). Artificial neural network. University of Zagreb, Zagreb. [20] Beale, M.H., Hagan, M.T., Demuth, H.B. (2010). Neural Network Toolbox 7: User’s Guide, The Mathworks, Natick.

Bajić, D, – Celent, L. – Jozić, S.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 683-690 DOI:10.5545/sv-jme.2012.730

Investigation on Machining Performance of Inconel 718 under High Pressure Cooling Conditions Çolak, O. Oğuz Çolak*

Süleyman Demirel University, Technology Faculty, Department of Manufacturing Engineering, Turkey The paper deals with experimental investigation on machinability of Inconel 718 in conventional and alternative high pressure cooling conditions. The experiments are designed according to Taguchi L18 orthogonal array based on three levels of cutting speed, feed rate and fluid pressure and two levels of depth of cut. The cutting forces and tool flank wear were measured, while turning Inconel 718 workpieces, using (Ti, Al)N+TiN coated CNMG0812 carbide cutting tools. In order to determine the importance of cutting parameters on tool flank wear and cutting forces, ANOVA (Analysis of variance) was employed. Moreover, with multi regression analysis, empirical equations that indicate relation between tool flank wear and cutting forces with machining parameters were defined. The experiment results have proven that the tool flank wear and cutting forces considerably decrease with the delivery of high pressure coolant to the cutting zone. Moreover, ANOVA results also indicate that high pressure cooling has a significant beneficial effect on cutting tool life. Keywords: High pressure assisted machining, ANOVA, Taguchi

0 INTRODUCTION Nickel-based alloys are the most widely used superalloys, accounting for about 50 wt.% of materials used in an aerospace engines, mainly in the gas turbine compartment (combustion part of the jet engine). They provide higher strength to weight ratio compared to steels. The use of nickel-based alloys in such aggressive environments hinges on the face that it maintains high resistance to corrosion, mechanical and thermal fatigue, mechanical and thermal shock, creep and erosion, at elevated temperatures [1] and [2]. Contrary to those superb properties, machining of nickel-based alloys generate high temperatures at the cutting tool edge, impairing their performance as they are subjected to high compressive stresses acting on the tool tip. This leads to the plastic deformation of the tool edge, severe notching and flank wear [3] to [5]. The poor thermal conductivity of nickel-based alloys, raises temperature at the tool–workpiece interface during machining, thus, it accelerates the undesired tool wear and results in the shortening of cutting tool life [6] and [7]. In order to keep increasing the machining performance, different assistance methods have been recently developed to replace the “conventional process” [8] and [9]. One of them presents highpressure jet assistance (HPJA), which aims at upgrading conventional machining, using the thermal and mechanical properties of a high-pressure jet of water or emulsion directed into the cutting zone [10] to [12]. By applying a high-pressure fluid jet to the cutting zone, it is possible to achieve advantages such

as significantly decreased temperature in the cutting zone, prolonged tool life (5 to 15 times), lower forces due to better frictional conditions between the tool face and the chip, and lower levels of vibration [12] to [14]. These results have also shown improved surface integrity and better dimensional accuracy of the produced parts [15] and [16]. HPJA also decreases the contact length between the chip and rake face [10]. The shorter contact length and lower friction force cause a larger shear plane angle, and thus reduce the chip-compression factor [17]. Currently, a major problem associated with conventional machining of super-alloys is the accelerated tool wear, resulting from generated hightemperature in the cutting zone. The use of highpressure jet-assisted cooling technology during the machining of super-alloys, provides temperature reduction at the cutting zone. This can be understood as a consequence of improved access of coolant closer to the cutting tool edge. This can significantly improve the tool life due to lower tool wear rates. Additionally, cutting speeds can be increased for up to 50% with the added advantage of effective chip breakability [1], [6] and [10]. Courbon et al. [10] studied machining performance of Inconel 718 under high pressure jet cooling conditions. They used coolant pressure in the range 50 to 130 MPa and three nozzle diameters (0.25, 0.3 and 0.4 mm). The experiments were conducted by using PVD TiAlN-coated carbide tools at various cutting speeds and feed rates, and at constant depth of cut (ap = 2 mm). They found that high pressure jet cooling provides better chip breakability and lower cutting forces. It can also improve surface finish and

*Corr. Author’s Address: Süleyman Demirel University, Technology Faculty, Department of Manufacturing Engineering, 32260, Isparta, Turkey, oguzcolak@sdu.edu.tr

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productivity for optimal pressure/ nozzle diameter/ cutting speed combination. Palanisamy et al. [18] investigated the effect of coolant pressure on chip formation and tool life, while turning Ti6Al4V alloy with uncoated straight tungsten carbide inserts. The investigation showed that the application of high pressure coolant directly between the chip back face and the tool results generally in smaller chips and average chip thickness compared to conventional pressure (0.6 MPa). They also found that the application of high pressure coolant prolongs tool life by nearly three times. This study mainly focuses on the evaluation of the cutting tool wear and wear characteristics, cutting force components and chip shape, while machining Inconel 718 under the high pressure and conventional cooling conditions. Therefore, a number of machining tests with Inconel 718 were conducted in conventional and various high pressure levels of cooling/lubrication fluid. The experiments were designed according to the plan of experiments methodologies and Taguchi L18 orthogonal array [19], at three different cutting speed (Vc), feed rate (f) and pressure (p) levels, and two different depth of cut (ap) levels. Experimental results, namely cutting forces (Fc, Fr , Ff ) and the average tool flank wear (Vb) were analyzed by using ANOVA and regression analysis. As a result of ANOVA, the effects of test parameters (Vc , f, p, ap) on average tool flank wear and cutting forces were statistically determined. Finally, multi regression equations that indicate the relation between cutting forces, tool flank wear and test parameters were obtained and used as a model for the HPJA machining process.

1.2 Experimental Set-Up and Equipment The experiments were conducted on ALEX ANL-75 CNC lathe machine that is equipped with variable spindle speed from 50 to 4000 rpm and a 15 kW motor drive that is equipped with the high-pressure plunger pump of maximum 35 MPa pressure and 21 l/min volumetric flow rate capacity (Fig. 1). The cooling/ lubrication fluid (CLF) used in the experiments was the chemical-based 5% concentration water soluble oil (Swisslube Blaser BCool 650). The high pressure CLF was injected between the cutting tool and formed chip back surface, at a low angle (about 5 to 6° with the cutting tool rake angle), as is shown in Fig. 1. A (Ti,Al)N+TiN coated carbide cutting tool CNMG0812 has been chosen for the experiments. The tool has rε = 0.8 mm nose radius. It was mounted on a SECO Jet stream PCLNR tool holder, which results in cutting rake angle, γa =-6°, back rake angle, γb = –6°, approach angle, Kr = 95°, and d = 0.8 mm nozzle diameter. All experiments were performed on machining nickel-based alloy Inconel 718 bar (63.5 mm diameter and 300 mm long). The standard chemical composition and mechanical properties of the workpiece are given in Tables 2 and 3, respectively [6]. The volume of totally removed material during each individual experiment was set to V = 57650.4 mm3 (according to the machining parameters and workpiece diameter, the cutting length was defined), and was kept constant for the sake of consistent tool wear comparison. In this way the wear can be directly related to the volume of cut material. 2 RESULTS AND DISCUSSIONS

1 EXPREMENTAL PROCEDURE

2.1 Cutting Forces

1.1 Design of Experiments

The results of experiments (cutting force components and average flank wear) are shown in Table 4. The influences of pressure and feed rate on cutting forces are illustrated in Figs. 2 to 4. The cutting forces generally increase with an increase in feed rate as expected. It can be also noticed that all the cutting force components decrease significantly with an increase in fluid pressure. This can be explained by the mechanical effect of the jet, which tends to lift up the chip, away from the tool rake face and reduces the contact area that is consistent with reference [10]. This has also been reported in [6], where a reduction in cutting forces when machining with assistance of high coolant pressure relates to the fact that high-pressure coolant is able to penetrate deeper into the cutting interface, thus, providing more efficient cooling as

The experiments designed based on Taguchi L18 orthogonal array at three different cutting speed, feed rate and pressure levels and two different depth of cuts are performed, while each one has been performed with a new cutting edge for the ease of direct comparability of results. Cutting parameters and their levels are shown in Table 1. Table 1. The levels of machining parameters Level Vc [m/min] f [mm/rev] p [MPa] ap [mm]

684

III

50 0.05 Conv. (0.6) 0.5

70 0.10 10 1

90 0.15 30 Çolak, O.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 683-690

Fig. 1. Experimental set-up, with the detailed view of high-pressure injection system Table 2. Chemical composition of Inconel 718 (wt.%) C 0.08

Mn 0.35

Si 0.35

S 0.15

Cr 18.6

Fe 17.8

Mo 3.1

Nb&Ta 5.0

Ti 0.9

Al 0.5

Cu 0.3

Ni balance

Table 3. Mechanical properties of Inconel 718 Tensile strength [MPa] 1310

Yield strength [MPa] 1110

Elastic modulus [GPa] 206

Hardness [HV150] 370

Density [g/cm3] 8.19

Melting point [°C] 1300

Thermal conductivity [W/(mK)] 11.2

Table 4. The experiment results No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

ap [mm] 0.5 0.5 1 1 0.5 1 0.5 0.5 0.5 1 1 1 0.5 0.5 1 1 0.5 1

Vc [m/min] 90 50 70 90 70 50 70 90 50 90 70 50 90 50 70 50 70 90

f [mm/rev] 0.15 0.05 0.15 0.10 0.05 0.10 0.10 0.05 0.10 0.15 0.05 0.15 0.10 0.15 0.10 0.05 0.15 0.05

p [MPa] 0.6 0.6 0.6 0.6 0.6 0.6 10 10 10 10 10 10 30 30 30 30 30 30

well as lubrication. The coolant water wedge created at the tool-chip interface reduces tool-chip contact length and forces, which can be also connected to benefits in friction conditions. According to the

Fc [N] 305.3 215 520.6 455.3 199.6 468.9 267 217 266 577.9 277.08 604.6 230 304.6 433 258.2 307.3 271.6

Ff [N] 137.9 113.6 287.2 375.4 149.6 370 138.4 171.25 134.1 379.5 218.1 362.8 109.62 128.2 288.1 159.14 124.6 214.77

Fr [N] 162.2 141 181 133.7 200.3 161 166.9 236.48 129.1 84.5 125 165.1 152.53 152 143.8 97.05 161.5 105.3

Vb [µm] 145 158.14 157.32 409.42 143 135.5 75 113.82 76.02 378.65 61.58 183.39 94.03 65.9 102.31 131.62 53.12 108.41

experiment results no significant effect of cutting speed Vc has been observed on the cutting force which is in agreement with experiments of Devillez et al. [20].

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cooling conditions in comparison to conventional cooling. Figs. 8 and 9 show flank and crater wear on cutting tool after constant removal of material volume. It can be seen that during the experiments also crater wear on cutting tool appeared on the rake face. Dahlman and Escursell [22] have reported that crater wear normally appears due to the abrasive and diffusion wear mechanisms. On the one hand,

2.2 Chip Formation After each experiment, the chips were collected and analyzed. Fig. 7 shows chip formation in various cutting conditions. It can be seen that turning of Inconel 718 with lower coolant pressure (p = 0.6 and 10 MPa) produced long continuous spiral chips, while smaller segmented chips were produced when machining with higher coolant pressure (30 MPa). What can be observed from those results Ezugwu and Bonney [6] also reported. Actually, the coolant supply at high-pressure tends to lift up the chip after passing through the deformation zone, resulting in a reduction in the tool-chip contact length/area. This tends to enhance chip fragmentation, as the chip curl radius is reduced significantly, hence, maximum coolant pressure is restricted only to a smaller area on the chip. 2.3 Tool Wear Tool wear normally negatively influences cutting power, machining quality, tool life and machining cost. When tool wear reaches a certain value, it significantly increases the cutting force, causing vibration and rising cutting temperature, which can cause surface integrity deterioration and dimensional error greater than tolerance [21]. The distribution of the wear along the flank face was non-uniform as can be seen in Fig. 8. Additionally, Fig. 5 shows the effect of the cutting speed and feed rate on average tool flank wear (combination of abrasive and depth of cut notch wear) under the high pressure cooling conditions. It can be seen that average tool flank wear increases with an increase in cutting speed and feed rate as is expected. Tool wear rate reaches its maximum value with the upper value of cutting speed and feed rate. Fig. 6 shows the tool flank wear trend in relation to pressure and feed rate. It can be clearly seen that the pressure of delivered coolant strongly affects the tool flank wear. An increase in coolant pressure has a decreasing effect on the tool flank wear. Ezugwu and Bonney [6] have stated that a major cause of tool rejection when machining Inconel 718 are generated high temperatures in the tool-chip and tool-workpiece interfaces. The temperature is significantly reduced by administering coolant under high pressure directly to the cutting interface. This could, therefore, minimize and/or completely eliminate thermally related wear mechanisms. Therefore, tool performance tends to be primarily dependent on mechanical wear phenomena. This means that tool life can be dominantly prolonged when machining Inconel 718 under high pressure 686

Fig. 2. Effect of pressure and feed rate on the main force Fc (ap = 0.5 mm, Vc = 50 m/min)

Fig. 3. Effect of pressure and feed rate on the feed force Ff (ap = 0.5 mm, Vc = 50 m/min)

Fig. 4. Effect of pressure and feed rate on the passive force Fr (ap = 0.5 mm, Vc = 50 m/min) Ă&#x2021;olak, O.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 683-690

Fig. 5. Effect of cutting speed and feed rate on average tool flank wear (ap = 1 mm, p = 300 bar)

Fig. 6. Effect of coolant pressure and feed rate on average tool flank wear (ap = 1 mm, Vc = 90 m/min)

P = 6 bar, a = 1 mm, Vc = 70 m/min, f = 0.15 mm/rev

P = 6 bar, a = 0.5 mm, Vc = 70 m/min, f = 0.05 mm/rev

P = 100 bar, a = 1 mm, Vc = 50 m/min, f = 0.15 mm/rev

P = 100 bar, a = 0.5 mm, Vc = 50 m/min, f = 0.10 mm/rev

P = 300 bar, a = 0.5 mm, Vc = 50 m/min, f = 0.15 mm/rev

P = 300 bar, a = 1 mm, Vc = 50 m/min, f = 0.05 mm/rev

Fig. 7. Chip formation at various pressure levels

excessive crater wear can lead to deterioration in chip formation because the chip breaker geometry is destroyed; on the other hand, high pressure coolant reduces the contact length between chip and tool. As a consequence, the tool is less worn on the rake face. 2.4 ANOVA Results In order to observe the influence of the experiment parameters on cutting force components and

average tool flank wear, ANOVA was employed. Statistical significance of the fitted model and terms was evaluated by the P-values of ANOVA. Values are given in Tables 5 to 8 for Fc, Ff, Fr and Vb, respectively. When P-values are less than 0.05 (or 95% confidence), the obtained models/parameters are considered to be statistically significant [23]. This demonstrates that the terms chosen in the model have significant effects on the responses.

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P = 100 bar, a = 1 mm, Vc = 90 m/min, f = 0.05 mm/rev

P = 6 bar, a = 2 mm, Vc = 90 m/min, f = 0.1 mm/rev

P = 300 bar, a = 1 mm, Vc = 90 m/min, f = 0.1 mm/rev

Fig. 8. Maximum and average flank wear on cutting tool at various cutting conditions (volume of material removed is kept constant V = 57650.4 mm3)

P = 6 bar, a = 1 mm, Vc = 50 m/min, f = 0.05 mm/rev

P = 100 bar, a = 1 mm, Vc = 90 m/min, f = 0.05 mm/rev

P = 300 bar, a = 2 mm, Vc = 90 m/min, f = 0.05 mm/rev

Fig. 9. Crater wear on cutting tool at various cutting conditions (volume of material removed is kept constant V = 57650.4 mm3) Table 5. ANOVA results for main cutting force Model ap Vc F P ap x Vc ap x f ap x p Vc x f Vc x p fxp Error Total

Sum of Degree of squares freedom 284214.600 10 80002.160 1 0.513 1 64510.420 1 1303.922 1 181.055 1 10881.860 1 602.878 1 482.380 1 126.812 1 1459.077 1 4911.447 7 289126.000 17

Mean F value square 28421.456 40.507 80002.162 114.022 0.513 0.001 64510.417 91.943 1303.922 1.858 181.055 0.258 10881.858 15.509 602.878 0.859 482.380 0.687 126.812 0.181 1459.077 2.079 701.635

Table 6. ANOVA results for passive force P

0.0001 0.0001 0.9792 0.0001 0.2150 0.6271 0.0056 0.3848 0.4344 0.6835 0.1925

Model ap Vc F P ap x Vc ap x f ap x p Vc x f Vc x p fxp Error Total

Table 5 shows ANOVA results for the main cutting force. It can be seen that depth of cut (ap) and feed rate (f) are the most significant terms influencing the main cutting force (P = 0.0001). Their interaction (ap×f) exhibits significant effect on main cutting force as well (P = 0.0056). 688

Sum of squares 19393.120 1243.507 189.365 26.534 1504.486 4799.427 574.266 69.866 4504.463 259.656 476.420 3041.725 22434.840

Degree of freedom 10 1 1 1 1 1 1 1 1 1 1 7 17

Mean square 1939.312 1243.507 189.365 26.534 1504.486 4799.427 574.266 69.866 4504.463 259.655 476.420 434.5321

F value

4.463 2.862 0.436 0.061 3.462 11.045 1.322 0.161 10.366 0.597 1.096

0.0297 0.1345 0.5303 0.8119 0.1051 0.0127 0.2881 0.7004 0.0147 0.4648 0.3299

Table 6 shows ANOVA results for passive force. It can be seen that the interaction between depth of cut and cutting speed (ap×Vc, P = 0.0127), and interaction between cutting speed and feed rate (Vc×f, P = 0.0147) have significant effect on passive force. The other terms and their interaction have no effect on passive Çolak, O.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, 683-690

force. Further, as seen in Table 7 depth of cut has the most significant effect on feed force (P = 0.0001). Feed rate (P = 0.0272) and pressure (P = 0.0153) do not have as a significant effect as the depth of cut on passive force component. Table 8 exhibits ANOVA results for average tool flank wear. It can be seen that fluid pressure has the most significant effect on tool flank wear (P = 0.0134). Table 7. ANOVA results for feed force Model ap Vc F P Error Total

Sum of squares 146844.700 116441.700 1212.030 12919.270 16271.640 27138.040 173982.700

Degree of freedom 4 1 1 1 1 13 17

Mean square 36711.165 116441.730 1212.030 12919.266 16271.635 2087.541

F value

17.586 55.779 0.581 6.189 7.795

0.0001 0.0001 0.4597 0.0272 0.0153

Table 8. ANOVA results for tool flank wear Model ap Vc F P Error Total

Sum of squares 107830.800 16210.200 34022.490 13804.760 43793.350 69665.970 177496.800

Degree of freedom 4 1 1 1 1 13 17

Mean square 26957.701 16210.202 34022.490 13804.762 43793.349 5358.921

F value

5.030 3.025 6.349 2.576 8.172

0.0113 0.1056 0.0256 0.1325 0.0134

Cutting speed (P = 0.0256) also has a significant effect on tool wear as expected. As a result of regression analysis, empirical equations have been obtained with R2 = 0.98, 0.86, 0.84 and 0.60, respectively. Equations are presented in Eq. 1. Fc = 81.25 + 77.20 a p + 1.28 Vc − 93.55 f − −0.70 p − 0.84 a pVc + 3211.19 a p f +

+0.28 a p p − 8.70 Vc f + 0.001 Vc p + 2.94 fp ,

In this study, machinability of Inconel 718 was experimentally investigated, comparing conventional with various high pressure cooling conditions on CNC lathe. The experiments are designed based on Taguchi L18 orthogonal array at three different levels of cutting speed, feed rate and pressure and two levels of depth of cut. During the experiments, cutting force components and tool flank wear were recorded. The results were analyzed by using ANOVA. Regression modeling was also used to investigate the relationships between process parameters and machining responses. The following conclusions can be drawn from this work: 1. The application of high pressure cooling/ lubrication fluid to the tool-chip interface decreases cutting force components on account of mechanical effect of high pressure coolant. 2. High pressure cooling improves and provides desirable chip breakability, which tends to improve the quality of machined surface. 3. Cutting tool wear, especially flank face wear, reduce with applying high pressure coolant to the tool-chip interface. This can be attributed to the fact that high pressure coolant provides better lubrication and cooling than conventional cooling. In addition, HPJA also helps to reduce tool-chip contact length and so helps in prolongation of tool life. 4. The high pressure coolant technique supports the sustainability directions in manufacturing, especially hard-to-cut materials, by increasing tool life and reducing the cutting forces resulting in higher productivity and lower energy consumption. 5. Sustainability can be supported even by the possibility of using less concentrated emulsions in HPJA machining (more water based CLF), which cause fewer health and environmental problems. 4 ACKNOWLEDGEMENTS

Fr = 166.87 + 168.71 a p + 6.47 Vc − 1095.00 f − −0.18 p − 4.35 a pVc + .737.68 a p f +

3 CONCLUSIONS

(1)

+0.09 a p p − 26.60 Vc f + 0.002 Vc p + 1.68 fp , Ff = −94.32 + 321.72 a p + 0.5 Vc − 656.23 f − 0.24 p , Vb = −134.43 + 120.03 a p + 2.66 Vc − 678.35 f − 0.40 p .

This project was supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK-108M380 Project) and Slovenian Research Agency (ARRS). The authors would like to thank also to SECOTOOLS, BLASER SwissLube and TAI-TUSAŞ A.Ş. companies for their support of this study.

Investigation on Machining Performance of Inconel 718 under High Pressure Cooling Conditions

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Manufacture, vol. 49, no. 2, p. 182-198, DOI:10.1016/j. ijmachtools.2008.08.008. [13] Klocke, F., Sangermann, H., Krtamer, A., Lung, D. (2011). Influence of a high pressure lubricoolant supply on thermo-mechanical tool load and tool wear behaviour in the turning of aerospace materials. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 225, no. 1, p. 52-61. [14] Pušavec, F., Kopač, J. (2011). Sustainability assessment: Cryogenic machining of Inconel 718. Strojniški vestnik - Journal of Mechanical Engineering, vol. 57, no. 9, p. 637-647, DOI:10.5545/sv-jme.2010.249. [15] Ezugwu, E.O., Bonney, J., Da Silva, R.B., Çakir, O. (2007). Surface integrity of finished turned Ti6Al4V alloy with PCD tools using conventional and high pressure coolant supplies. International Journal of Machine Tools & Manufacture, vol. 47, no. 6, p. 884891, DOI:10.1016/j.ijmachtools.2006.08.005. [16] Adamczak, S., Čuš, F., Miko, E. (2009). A model of surface roughness constitution in the metal cutting process applying tools with defined stereometry. Strojniški vestnik - Journal of Mechanical Engineering, vol. 55, no. 1, p. 45-54. [17] Kaminski, J., Alvelid, B. (2000). Temperature reduction in the cutting zone in water-jet assisted turning. Journal of Materials Processing Technology, vol. 106, no. 1-3, p. 68-73, DOI:10.1016/S0924-0136(00)00640-3. [18] Palanisamy, S., McDonald, S.D., Dargusch, M.S. (2009). Effects of coolant pressure on chip formation while turning Ti6Al4V alloy. International Journal of Machine Tools & Manufacture, vol. 49, no. 9, p. 739743, DOI:10.1016/j.ijmachtools.2009.02.010. [19] Krajnik, P., Kopač, J., Sluga, A. (2005). Design of grinding factors based on response surface methodology. Journal of Materials Processing Technology, vol. 162-163, p. 629-636, DOI:10.1016/j. jmatprotec.2005.02.187. [20] Devillez, A., Schneider, F., Dominiak, S., Dudzinski, D., Larrouquere D. (2007). Cutting forces and wear in dry machining of Inconel 718 with coated carbide tools. Wear, vol. 262, no. 7-8, p. 931-942, DOI:10.1016/j. wear.2006.10.009. [21] Kamruzzaman, M., Dhar, N.R. (2009). The influence of high pressure coolant on temperature tool wear and surface finish in turning 17CrNiMo6 and 42CrMo4 steels. Journal of Engineering and Applied Sciences, vol. 4, no. 6, p. 93-103. [22] Dahlman, P., Escursell, M. (2004). High-pressure jetassisted cooling: a new possibility for near net shape turning of decarburized steel. International Journal of Machine Tools & Manufacture, vol. 44, no. 1, p. 109115, DOI:10.1016/S0890-6955(03)00058-0. [23] Stamatis, D.H. (2003). Six Sigma and Beyond. ST. Lucie Press, New York.

5 REFERENCES [1] Ezugwu, E.O., Bonney, J., Yamane, Y. (2003). An overview of the machinability of aeroengine alloys. Journal of Materials Processing Technology, vol. 134, no. 2, p. 233-253; DOI:10.1016/S0924-0136(02)010427. [2] Pušavec, F., Krajnik, P., Kopač, J. (2006). High-speed cutting of soft materials. Strojniški vestnik - Journal of Mechanical Engineering, vol. 52, no. 11, p. 706-722. [3] Župerl, U., Čuš, F. (2004). A determination of the characteristic technological and economic parameters during metal cutting. Strojniški vestnik - Journal of Mechanical Engineering, vol. 50, no. 5, p. 252-266. [4] Župerl, U., Čuš, F., Gečevska, V. (2007). Optimization of the characteristic parameters in milling using the pso evaluation technique. Strojniški vestnik - Journal of Mechanical Engineering, vol. 53, no. 6, p. 354-368. [5] Čuš, F., Župerl, U., Kiker, E. (2007). A modelbased system for the dynamic adjustment of cutting parameters during a milling process. Strojniški vestnik - Journal of Mechanical Engineering, vol. 53, no. 9, p. 524-540. [6] Ezugwu, E.O., Bonney, J. (2004). Effect of highpressure coolant supply when machining nickel-base, Inconel 718, alloy with coated carbide tools. Journal of Materials Processing Technology, vol. 153-154, p. 1045-1050, DOI:10.1016/j.jmatprotec.2004.04.329. [7] Pušavec, F., Kramar, D., Krajnik, P., Kopač, J. (2010). Transition to sustainable production - part ii: Evaluation of sustainable machining technologies. Journal of Cleaner Production, vol. 18, no. 12, p. 1211-1221, DOI:10.1016/j.jclepro.2010.01.015. [8] Pušavec, F., Krajnik, P., Kopač, J. (2010). Transition to sustainable production – Part I: Application on machining technologies. Journal of Cleaner Production, vol. 18, no. 2, p. 174-184, DOI:10.1016/j. jclepro.2009.08.010. [9] Sharma, V.S., Dogra, M., Suri, N.M. (2009). Cooling techniques for improved productivity in turning. International Journal of Machine Tools & Manufacture, vol. 49, no. 6, p. 435-453, DOI:10.1016/j. ijmachtools.2008.12.010. [10] Courbon, C., Kramar, D., Krajnik, P., Pušavec, F., Rech, J., Kopač, J. (2009). Investigation of machining performance in high-pressure jet assisted turning of Inconel 718: An experimental study. International Journal of Machine Tools & Manufacture, vol. 49, no. 11, p. 1114-1125, DOI:10.1016/j. ijmachtools.2009.07.010. [11] Kramar, D., Krajnik, P., Kopač, J. (2010). Capability of high pressure cooling in the turning of surface hardened piston rods. Journal of Materials Processing Technology, vol. 210, no. 2, p. 212-218, DOI:10.1016/j. jmatprotec.2009.09.002. [12] Nandy, A.K., Gowrishankar, M.C., Paul, S. (2009). Some studies on high-pressure cooling in turning of Ti–6Al–4V. International Journal of Machine Tools &

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Çolak, O.

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11 Vsebina

Vsebina Strojniški vestnik - Journal of Mechanical Engineering letnik 58, (2012), številka 11 Ljubljana, november 2012 ISSN 0039-2480 Izhaja mesečno

Razširjeni povzetki člankov Samo Venko, Boris Vidrih, Erik Pavlovič, Sašo Medved: Izboljšan prenos toplote na toplotno aktivirani hlajeni steni Jiang Ding, Yangzhi Chen, Yueling Lv: Snovanje zobnikov s cilindričnimi zobmi neenakega polmera in prostorsko ubirnico Ranko Božičković, Milan Radošević, Ilija Ćosić, Mirko Soković, Aleksandar Rikalović: Integracija orodij za simulacijo in vitkost v učinkovitih sistemih proizvodnje – študija primera Robert Iacob, Diana Popescu, Peter Mitrouchev: Analiza montaže/demontaže in tehnike modeliranja: pregled Baoping Cai, Yonghong Liu, Congkun Ren, Aibaibu Abulimiti, Xiaojie Tian, Yanzhen Zhang: Probabilistična toplotna in elektromagnetna analiza podmorskih elektromagnetnih ventilov za preprečevalnike izbruha Dražen Bajić, Luka Celent, Sonja Jozić: Modeliranje vpliva rezalnih parametrov na površinsko hrapavost, obrabo orodja in rezalne sile pri čelnem rezkanju za off-line (posredno) krmiljenje procesa Oğuz Çolak: Raziskava obdelovalnosti Inconela 718 v pogojih visokotlačnega hlajenja

SI 138 SI 139

Osebne vesti Doktorske disertacije, znanstvena magistrska dela, diplomske naloge

SI 140

SI 133 SI 134 SI 135 SI 136 SI 137

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 133

Izboljšan prenos toplote na toplotno aktivirani hlajeni steni Venko, S. – Vidrih, B. – Pavlovič, E. – Medved, S. Samo Venko1,* – Boris Vidrih2 – Erik Pavlovič1 – Sašo Medved2 1 Hidria

2 Univerza

IMP Klima d.o.o., Slovenija v Ljubljani, Fakulteta za strojništvo, Slovenija

Podnebne spremembe, mikroklimatski pogoji v urbanih področjih in trend staranja prebivalstva bodo vplivali na rabo energije za hlajenje stavb pri zagotavljanju bivalnega ugodja. Zato bo potrebno uporabiti nove tehnologije, ki bodo za delovanje rabile manj energije od trenutno uporabljenih rešitev. Velik potencial za hlajenje predstavljajo toplotno aktivirane gradbene konstrukcije, saj omogočajo uporabo naravnih virov, kot so podtalnica, navpični in horizontalni zemeljski prenosniki toplote in hladilni stolpi za visokotemperaturno hlajenje. Kljub mnogim prednostim imajo ti sistemi tudi slabosti, ki jih je možno učinkoviti izboljšati z načinom vpihovanja vtočnega zraka v prostor skozi linijsko odprtino, ki je postavljena neposredno ob hlajeno steno. Vpihovanje vtočnega zraka povzroči nastanek procesa mešane konvekcije, kar poveča konvektivni prenos toplote na hlajeni steni v primerjavi z naravno konvekcijo. V dostopni literaturi avtorji niso našli modelov za vrednotenje takega način konvektivnega prenosa toplote na hlajeni steni, zato so z uporabo računalniške dinamike tekočin razvili empirične modele v obliki večfunkcijskih polinomov za lokalno in povprečno toplotno prestopnost za naravno in izboljšano (mešano) konvekcijo. Predstavljeni modeli za naravno konvekcijo na hlajeni steni veljajo v območju 2,5 ≤ Δϑ ≤ 20 °C, kjer je temperaturna razlika Δϑ opredeljena z razliko srednje temperature zraka v prostoru in površinske temperature stene, medtem ko je v modelu za mešano konvekcijo kot temperaturna razlika upoštevana razlika med temperaturo vtočnega zraka in temperaturo hlajene stene. Razviti empirični modeli so bili uporabljeni v orodju TRNSYS za napoved učinka hlajenja z mehanizmom mešane konvekcije na hlajeni steni tipičnega pisarniškega prostora velikosti 5×6×3 m. V različnih scenarijih, ki so upoštevali tri stopnje hladilnih obremenitev (30, 45 in 60 W/m2) in različne načine prezračevanja, sta bili obravnavani dve različni širini aktivirane stene 3 in 6 m, v vseh scenarijih pa je bila površinska temperatura toplotno vzbujene stene enaka 17 °C. Učinkovitost hlajenja je bila vrednotena s kriterijem CDH (cooling degree hours) oz. urnim temperaturnim presežkom, ki predstavlja vsoto produktov časa, ko je presežena referenčna temperatura, in temperaturne razlike med notranjo občuteno temperaturo in referenčno temperaturo. Za vrednotenje toplotnega ugodja je bil uporabljen adaptivni model Kategorije A po literaturi. V članku je pokazano, da se z izboljšano toplotno prestopnostjo kompenzira nizke hladilne obremenitve (30 W/m2) s 3 m široko toplotno aktivirano steno pri hitrosti vtočnega zraka 2 m/s. Enaka dolžina aktivirane stene omogoča tudi kompenzacijo srednjih hladilnih obremenitev (45 W/m2), vendar pri hitrosti vtočnega zraka 4 m/s. V primeru prenosa toplote z naravno konvekcijo ne zadostuje niti večja toplotno aktivirana stena dolžine 6 m. V tem primeru se očitno prepozna prednost uporabe vtočnega zraka za izboljšanje toplotne prestopnosti na hlajeni steni. Tudi visoke hladilne obremenitve (60 W/m2) je skoraj v celoti možno kompenzirati z vpihovanjem vtočnega zraka s hitrostjo vSA = 4 m/s ob toplotno aktivirani steni širine 6 m. Kombinacija toplotno aktiviranih konstrukcij in naravne konvekcije sicer ne povzroča emisij hrupa, vendar je hladilna moč zelo odvisna od temperaturne razlike med površino in zrakom v bližini površine. Ob tem se hlajenje z naravno konvekcijo težko uravnava, saj je možno hladilno moč prilagajati le s počasi odzivnim spreminjanjem površinske temperature. Zato ima hlajenje s povečanim prenosom toplote s pomočjo curka zraka ob toplotno vzbujeni steni izrazite prednosti pred sistemi z naravno konvekcijo. Ključne besede: aktivno naravno hlajenje, toplotno aktivirane gradbene konstrukcije, izboljšan konvektivni prenos toplote, toplotno ugodje, numerično modeliranje prenosa toplote

*Naslov avtorja za dopisovanje: Hidria IMP Klima d.o.o., Godovič 150, SI-5275 Godovič, Slovenija, samo.venko@hidria.com

SI 133

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 134

Snovanje zobnikov s cilindričnimi zobmi neenakega polmera in prostorsko ubirnico Ding, J. –Chen, Y. –Lv, Y. Jiang Ding –Yangzhi Chen* –Yueling Lv Tehniška univerza Južne Kitajske, Kitajska

V zadnjih letih se je uveljavil zobniški mehanizem s prostorsko ubirnico SCMW. Zobniški mehanizem je namesto s tradicionalno ubirno površino oblikovan po teoriji prostorske ubirnice. Prenos z zveznim stikom točk dveh konjugiranih krivulj ima prednosti kot so veliko prestavno razmerje, majhna velikost in majhna teža. Mehanizem SCMW se je po letih raziskav enačb prostorskih ubirnic, stopnje prekritja, konstrukcijskih kriterijev in proizvodnih postopkov uveljavil predvsem pri aplikacijah kot so mikroreduktorji. Vse objavljene raziskave pa so bile omejene na zobe enakega polmera. Enačbe prostorske ubirnice so odvisne od polmera zob, zato morajo biti pari zobnikov SCMW ustrezno usklajeni. V članku je predstavljena metoda za snovanje zobnikov SCMW z neenakimi polmeri zob za uporabo v industriji. Kontaktne površine zobnikov SCMW so običajno gladke in vitke oblike, npr. cilindrični zobje. Natančneje, dva invariantna kroga sta si v vsakem trenutku tangentna v točki ubiranja. Središči krogov se nahajata na liniji kontaktnega vektorja in na nasprotnih straneh točke ubiranja. Ko je dokončan cel cikel ubiranja, kroga oblikujeta valjasto obliko pogonskega in gnanega zoba. Kroga različnega premera tvorita cilindrične zobe različnih premerov. Načela snovanja, predstavljena v tem članku, omogočajo celo oblikovanje zob variabilnega premera. Snovanje je osredotočeno na krivulje ubiranja in predlagana je kinematična enačba, ki je povezana samo z lastnostmi kontaktnih krivulj in njihovimi kinematičnimi razmerji, ne pa tudi s polmeri zob. Polmeri zob gnanega in pogonskega zobnika so zato neodvisni. Nato so izračunane krivulje ubirnice in krivulje središč za teoretično opredelitev zobnikov SCMW z zobmi neenakega polmera. Teorija snovanja je podrobno pojasnjena na primeru. Pogonska ubirnica je vijačnica, gnana ubirnica pa je konična vijačnica. Metoda je nato bila preizkušena s simulacijo in praktičnim eksperimentom po podatkih iz prejšnjega primera. Vzorci zobnikov SCMW z zobmi neenakega premera so bili izdelani po postopku selektivnega laserskega nataljevanja (SLM) in preizkušeni na eksperimentalnem sistemu, ki ga je zgradila naša raziskovalna skupina. Med ubiranjem se beleži položaj zob ter merijo in analizirajo povprečna prestavna razmerja. Analiza rezultatov kaže, da je metoda zanesljiva. Predstavljena metoda ima dve prednosti v primerjavi z obstoječimi metodami snovanja: 1) Polmera pogonskega in gnanega zobnika ne vplivata na proces ubiranja, zato ju je mogoče določati neodvisno drug od drugega z ozirom na zahteve aplikacije. 2) Podaja teoretične osnove za optimizacijo oblike zob glede na pogoj trdnosti. Metoda omogoča tudi snovanje zobnikov SCMW z variabilnim polmerom in konstantnimi obremenitvami. Z razširjenimi možnosti snovanja zobnikov SCMW z zobmi neenakega polmera se odpira potreba po ugotavljanju razmerja med napetostmi in polmeri za določitev optimalnih polmerov. Pravila za izbiro oblik bodo določena pozneje. Ključne besede: zobnik, prostorska ubirnica SCMW, zobje neenakega polmera, ubirnica, kinematična enačba, cilindrični zobje

SI 134

*Naslov avtorja za dopisovanje: Visoka šola za strojništvo, Tehniška univerza Južne Kitajske, Wushan,Tianhe, Guangzhou, Kitajska, meyzchen@scut.edu.cn

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 135

Integracija orodij za simulacijo in vitkost v učinkovitih sistemih proizvodnje – študija primera

Božičković, R. – Radošević, M. – Ćosić, I. – Soković, M. – Rikalović, A. Ranko Božičković1 – Milan Radošević2,* – Ilija Ćosić2 – Mirko Soković3 – Aleksandar Rikalović2 1 Univerza

v vzhodnem Sarajevu, Fakulteta za transport in promet, Bosna in Hercegovina 2 Univerza v Novem Sadu, Fakulteta tehniških znanosti, Srbija 3 Univerza v Ljubljani, Fakulteta za strojništvo, Slovenija

Namen tega prispevka je prikazati proizvodne sisteme, ki so s svojo strukturo zasnovani v skladu z načeli grupne tehnologije in jih je treba, kljub njihovi popolnosti, hitro prilagajati spremembam v okolju in sodelovanju v boju s konkurenco. Najprej morajo biti tesno povezani s kupci in dobavitelji, kar predstavlja eno prvih načel filozofije vitkosti. To je eden od načinov za uspešno ovrednotenje primerjalne prednosti pred konkurenco, kljub njihovemu notranjemu prestrukturiranju. Opredelitev problema in glavna zamisel tega prispevka sta potekali v dveh smereh: prva naj bi v obstoječih ali podobnih okoliščinah pomagala pri kritični oceni in z uporabo novih predlogov za izboljšanje učinkovitosti z uporabo konceptov vitkosti pomagala pri doseganju konkurenčnosti na globalnem trgu. Druga smer nakazuje povečanje učinkovitosti in uspešnosti proizvodnih sistemov ter zmanjšanje zalog in skrajšanje proizvodnega cikla v primerjavi z začetnim stanjem. V prispevku je pokazano, da je z uveljavitvijo nekaterih orodij vitkosti, kakor tudi z uporabo statističnih analiz, simulacij in grafičnih orodij, mogoče doseči večjo učinkovitost in uspešnost proizvodnih sistemov. Opisan je tudi razvoj sistematične metodologije za izvajanje koncepta vitkosti v industrijskih sistemih. Metodologija v tem članku prikazuje uporabo in povezovanje grafične programske opreme (Sigma pretoka VSM), simulacijske programske opreme (Simul8) in statističnega programa (Minitab), realiziranega v industrijskem sistemu za proizvodnjo gibkih cevi. Sistem je bil v preteklosti določen na podlagi grupne tehnologije in izdelkov iz tega industrijskega sistema, ki so bili razvrščeni v skupine glede na klasifikacijski sistem KS-IIS-08. Rezultati uporabe in integracije teh orodij omogočajo skrajšanje proizvodnega ciklusa, zmanjšanje stopnje zahtevnosti materialnih tokov, zmanjšanje zalog in stroškov energetskih virov, medtem ko ustvarjajo povečano stopnjo funkcionalnosti organizacije, izrabo delovnega prostora itd., kot je predstavljeno v diskusiji tega članka. Glavne omejitve in posledice, ki so se pokazale med raziskavo, so nastale zaradi značilne nenaklonjenosti spremembam s strani zaposlenih, predvsem zaradi strahu pred izgubo svojih delovnih mest. Vendar je samo delo pokazalo, da se je učinkovitost povečala brez spremembe števila zaposlenih. Izvajanje raziskave v določenem časovnem obdobju je spodbudila zaposlene in druge kritike, da so v veliki meri spremenili svoje mnenje in tudi sprejeli spremembe v pozitivnem smislu. Vrednost tega prispevka je v tem, da s kombinacijo različnih predstavljenih orodij prikaže nov tehnološki, organizacijski in informacijski pristop k proizvodnji, ki bo zagotavljal še boljši položaj na trgu za industrijske sisteme. Z razvojem postopkov, korakov in faz izvajanja konceptov vitkosti na omenjenem področju obstajajo realne možnosti za nadaljnje raziskave, ki bodo vključevale koncept vitkosti in koncept učinkovitega sistema v enem integriranem konceptu za modeliranje proizvodnega sistema. Ključne besede: vitkost, učinkoviti sistemi, grupna tehnologija, simulacija

*Naslov avtorja za dopisovanje: Univerza v Novem Sadu, Fakulteta tehniških znanosti,Trg Dositeja Obradovica,21000 Novi Sad, Srbija; radosevic@uns.ac.rs

SI 135

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 136

Analiza montaže/demontaže in tehnike modeliranja: pregled Iacob, R. – Popescu, D. – Mitrouchev, P. Robert Iacob1,* – Diana Popescu1 – Peter Mitrouchev2 1 Politehnika

2 Laboratorij

v Bukarešti, Romunija G-SCOP, Grenoble, Francija

Optimizacija in realistična virtualna simulacija procesa montaže in demontaže je pomembna raziskovalna tema, če upoštevamo pomembno vlogo teh operacij tako v začetnih fazah snovanja izdelkov kakor tudi pri izdelavi, ergonomijo, usposabljanje, servis in recikliranje. Literatura poroča o številnih metodah za analizo in optimizacijo ter o različnih aplikacijah za simulacijo, ki uporabljajo koncept montažnih povezav oz. informacije o združevanju komponent. Tudi tehnologija navidezne resničnosti je v zadnjem desetletju dosegla novo raven dovršenosti in zdaj kombinira več vmesnikov med človekom in računalnikom, ki uporabniku zagotavljajo različne čute – vizualne, optične in haptične, da se ta lahko »potopi« v računalniško ustvarjeno platformo. Za ta namen so potrebne tudi nove faze priprave. Glavni cilj raziskave, predstavljene v članku, je predlog novih orodij za izboljšanje zmožnosti simulacije montaže/demontaže ter določitev načrta razvoja programske opreme, kot del tekočih raziskovalnih dejavnosti za ustvarjanje kompleksne virtualne simulacijske platforme za montažo. V ta namen je najprej podana primerjava modulov za montažo v programski opremi za analizo montaže/demontaže in simulacijskih platformah, ter orodij za modeliranje montaže v komercialni programski opremi za CAD. Preučeni so bili različni elementi: pogoji združevanja (geometrijske omejitve) komponent v sestave, funkcije za ustvarjanje stikov, ter orodja za zaznavanje trkov in ovir. Analiza obravnava tudi vrste informacij o relativni mobilnosti komponent, ki so na voljo v obstoječi programski opremi, ter način uporabe teh informacij. Glavni zaključek analize obstoječega stanja je, da trenutna programska oprema za analizo, platforme za simulacijo in CAD-programska oprema ne nudijo potrebnih informacij in vsestranskosti, potrebne za kompletno modeliranje in simulacijo procesa montaže/demontaže. To je izhodišče za načrt razvoja programske opreme za virtualno simulacijsko platformo za montažo, ki bo izboljšala proces simulacije montaže/demontaže in ga integrirala v različne faze življenjskega cikla izdelka. Predlagana simulacijska platforma bo zasnovana na novem konceptu: koncept vmesnika bo vključeval zaključen nabor podatkov o mehanskih stikih modela izdelka ter nov operator kinematične kombinacije, ki bo opisoval vse družine trajektorij, povezanih z vmesniki ali kinematičnimi pari različnih komponent izdelka. Simulacijska platforma bo morala za kompletno simulacijsko okolje imeti naslednjo strukturo: uvozni modul za uvoz 3D-modelov iz različnih programskih paketov za konstruiranje; vmesniški modul, ki bo sposoben samostojno identificirati geometrijske omejitve, relativni položaj kontaktnih površin in skupno območje, ter te podatke kombinirati v nabor vmesnikov za predmet; modul za mobilnost – primerno orodje za ustvarjanje mobilnosti komponente iz sestava glede na okolje; sekvenčni modul, ki bo lahko določil vrstni red montaže ali demontaže komponente izdelka ali celotnega izdelka; potopitveni modul, ki bo nudil realistično simulacijsko okolje v kombinaciji s haptično interakcijo; in izvozni modul za izvoz modelov s semantičnimi informacijami za nadaljnjo uporabo. Končno je predstavljena tudi prva implementacija platforme, ki je bila razvita za nekatere naloge analize montaže ter ilustrira koncepte in izvedljivost pristopa. Ključne besede: montaža/demontaža, navidezna resničnost, orodja za modeliranje, simulacija

SI 136

*Naslov avtorja za dopisovanje: Politehnika v Bukarešti, 313 Splaiul Independentei, Bukarešta 060042, Romunija; robert.iacob@gmail.com

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 137

Probabilistična toplotna in elektromagnetna analiza podmorskih elektromagnetnih ventilov za preprečevalnike izbruha

Cai, B. – Liu, Y. – Ren, C. – Abulimiti, A. – Tian, X. – Zhang, Y. Baoping Cai – Yonghong Liu* – Congkun Ren – Aibaibu Abulimiti – Xiaojie Tian – Yanzhen Zhang Fakulteta za strojništvo in elektrotehniko, Kitajska univerza za nafto, Kitajska

Članek obravnava raziskavo vpliva negotovosti materialnih lastnosti, fizičnih dimenzij in priključne napetosti na toplotne in elektromagnetne pojave z analizo po metodi končnih elementov (FEA), z namenom izboljšanja zmogljivosti podmorskih elektromagnetnih ventilov, vgrajenih v zaporne naprave za preprečevanje izbruha iz vrtin (angl. blowout preventer, BOP). Deterministična toplotna in elektromagnetna analiza po metodi končnih elementov je bila opravljena s programsko opremo ANSYS, probabilistične analize pa so bile izvedene z ANSYSovim sistemom za probabilistično snovanje (PDS). Vpliv negotovosti petih materialnih lastnosti, štirih fizičnih dimenzij in priključne napetosti na maksimalno temperaturo v ventilu in elektromagnetno silo v zračni reži je bil raziskan s simulacijo Monte Carlo in metodo odzivne površine. Za toplotno analizo so bile kot naključne vhodne veličine vzete materialne lastnosti, vključno s toplotno prevodnostjo jekla 316L, nerjavnega jekla 440C in prevodnega olja, koeficient konvektivnega prenosa toplote morske vode, fizične dimenzije vključno s polmerom bata, notranjim in zunanjim polmerom batne puše ter polmerom magnetnega obroča, in priključna napetost. Naključna izhodna veličina je maksimalna temperatura v ventilu. Za elektromagnetno analizo so bile kot naključni vhodni parametri uporabljene materialne lastnosti vključno z relativno permeabilnostjo nerjavnega jekla 440C, štiri fizične dimenzije in priključna napetost. Naključna izhodna veličina je bila maksimalna elektromagnetna sila. Rezultati deterministične analize so pokazali, da je maksimalna temperatura 97,16 °C v središču tuljave. Maksimalna temperatura je nižja od največje dovoljene temperature 120 °C. Minimalne temperature so na koncu ventila, proč od tuljave. Rezultati probabilistične toplotne analize kažejo, da imajo polmer magnetnega obroča, priključna napetost in toplotna prevodnost nerjavnega jekla 440C pomemben vpliv na maksimalno temperaturo podmorskega elektromagnetnega ventila. Te tri spremenljivke so odgovorne za skoraj tri četrtine vpliva na verjetnost okvare, ostalih šest spremenljivk pa za preostalo četrtino. Pri snovanju ventila je zato treba posvetiti več pozornosti tem trem spremenljivkam. Probabilistična elektromagnetna analiza je pokazala, da imata polmer bata in notranji polmer batne puše pomemben vpliv na elektromagnetno silo podmorskega elektromagnetnega ventila. Dve spremenljivki sta odgovorni za več kot tri četrtine vpliva na verjetnost okvare, ostale štiri spremenljivke pa za preostalo verjetnost. Pri konstruiranju ventila je zato treba več pozornosti posvetiti polmeru bata in notranjemu polmeru batne puše. Sprojektiran in izdelan je bil prototip podmorskega elektromagnetnega ventila za podmorske preprečevalnike izbruha. Za potrjevanje rezultatov analize po metodi končnih elementov sta bili izmerjeni temperatura v podmorskem elektromagnetnem ventilu in elektromagnetna sila kot funkcija zračne reže. Rezultati temperaturnih meritev kažejo, da imajo napovedane in eksperimentalne temperature podoben trend, napovedane temperature pa so nekoliko višje od eksperimentalnih. Rezultati potrjujejo pravilnost izračuna temperature s pomočjo ANSYS-a. Rezultati preizkusov elektromagnetne sile kažejo, da se napovedane sile dobro ujemajo z eksperimentalnimi, pri čemer so eksperimentalne rahlo višje od napovedanih. Rezultati potrjujejo pravilnost izračuna elektromagnetne sile s pomočjo ANSYS-a. Ključne besede: metoda končnih elementov, elektromagnetne sile, elektromagnetno segrevanje, verjetnost, ventili, podmorski elektromagnetni ventil

*Naslov avtorja za dopisovanje: Fakulteta za strojništvo in elektrotehniko, Kitajska univerza za nafto, Dongying, Shandong 257061, Kitajska, liuyh@upc.edu.cn

SI 137

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 138

Modeliranje vpliva rezalnih parametrov na površinsko hrapavost, obrabo orodja in rezalne sile pri čelnem rezkanju za off-line (posredno) krmiljenje procesa Bajić, D, – Celent, L. – Jozić, S. Dražen Bajić* – Luka Celent – Sonja Jozić

Univerza v Splitu, Fakulteta za elektrotehniko, strojništvo in ladjedelništvo, Hrvaška

Današnji kompleksni proizvodni in tehnološki procesi zahtevajo uporabo krmilnih sistemov, ki za učinkovito delovanje uporabljajo dovršene matematične in druge metode. Zato so potrebne raziskave, namenjene pridobivanju čim boljših matematičnih približkov obdelovalnih procesov in pojavov. Inženirji v proizvodnji se soočajo z dvema glavnima problemoma. Prvi je ugotavljanje vrednosti parametrov procesa, ki zagotavljajo doseganje pričakovane kakovosti izdelka, drugi pa je optimizacija zmogljivosti proizvodnega sistema z razpoložljivimi viri. Proces obdelave določajo medsebojna razmerja med vhodnimi veličinami, njegovo učinkovitost pa je mogoče meriti z izhodnimi veličinami. Veliko število vhodnih veličin in dejstvo, da se le-te kvantitativne in kvalitativne narave, pomenita množico možnih interakcij in njihovo kompleksnost. Namen te raziskave je poiskati matematične modele, ki povezujejo površinsko hrapavost, obrabo orodja in komponente rezalne sile s tremi parametri odrezavanja, t.j. rezalno hitrostjo (vc), podajanjem na zob (f) in globino reza (ap) pri čelnem rezkanju. Kljub dolgoletnim raziskavam in številnim zgodbam o uspehu v laboratoriju se le majhen del sodobne tehnologije prenese v proizvodnjo. Off-line (indirektno oz. posredno) krmiljenje procesa kot pristop, ki je primeren za praktično uporabo in ga je mogoče enostavno integrirati v obstoječih pogojih, je zato še vedno ključ za uspešno obdelavo ter predstavlja most med raziskavami in proizvodnjo. Raziskani so vplivi rezalne hitrosti, podajanja na zob in globine reza na površinsko hrapavost, obrabo orodja in rezalne sile v procesu čelnega rezkanja. Za modeliranje odvisnosti med temi parametri je bila uporabljena metoda regresijske analize in nevronskih mrež. Pridobljeni modeli so primerni za snovanje off-line krmiljenja procesa. V tej raziskavi sta bila uporabljena dva različna pristopa za izdelavo matematičnih modelov. Prvi pristop vključuje zasnovo eksperimenta (DOE) skupaj z analizo variance (ANOVA) in regresijsko analizo (RA), drugi pa modeliranje z umetnimi nevronskimi mrežami (ANN). Podana je tudi primerjava rezultatov obeh modelov. Vpliv treh rezalnih parametrov je mogoče določiti z opazovanjem sprememb površinske hrapavosti, obrabe orodja in komponent rezalne sile. Izračunana je bila tudi relativna napaka odstopanj od izmerjenih vrednosti kot merilo za to, katera metoda modeliranja daje boljše rezultate. Primerjane so bile relativne napake, dobljene z metodologijo RA in ANN, rezultati pa kažejo, da ima model ANN najboljšo sposobnost napovedovanja s skupno povprečno relativno napako 3,35 %. Matematični modeli so bili razviti za specifičen material obdelovanca ter geometrijo in material orodja. Eksperimenti so bili izvedeni v nadzorovanem laboratorijskem okolju in ponoviti bi jih bilo treba še v realnem proizvodnem okolju. Članek predstavlja prispevek k razvoju off-line krmiljenja procesov z vnaprejšnjo določitvijo spremenljivk procesa kot delom faze načrtovanja procesa. Rezultati kažejo, da je mogoče z obema metodologijama natančno napovedati površinsko hrapavost, obrabo orodja in komponente rezalne sile. Raziskava je pokazala, da so modeli z nevronskimi mrežami pri razmeroma majhnih učnih množicah (kot pri tej študiji) primerljivi z metodologijo RA in lahko dajejo celo boljše rezultate. Natančnejše napovedi izboljšajo off-line krmiljenje procesa za občutno zmanjšanje stroškov obdelave. Ključne besede: off-line (indirektno oz. posredno) krmiljenje procesa, površinska hrapavost, rezalna sila, obraba orodja, regresijska analiza, nevronska mreža z radialno osnovno funkcijo

SI 138

*Naslov avtorja za dopisovanje: Univerza v Splitu, Fakulteta za elektrotehniko, strojništvo in ladjedelništvo, Ruđera Boškovića 32, 21000 Split, Hrvaška, dbajic@fesb.hr

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 139

Raziskava obdelovalnosti Inconela 718 v pogojih visokotlačnega hlajenja Çolak, O. Oğuz Çolak*

Univerza Süleymana Demirela, Tehniška fakulteta, Katedra za proizvodno strojništvo, Turčija

Članek obravnava eksperimentalno raziskavo obdelovalnosti Inconela 718 v pogojih konvencionalnega in alternativnega visokotlačnega hlajenja. Eksperimenti so bili zasnovani po ortogonalnem polju Taguchi L18 na osnovi treh ravni rezalne hitrosti, podajanja in tlaka tekočine, ter dveh ravni globine reza. Izmerjene so bile rezalne sile in obraba bokov orodja pri struženju obdelovancev iz Inconela 718 s trdokovinskimi orodji CNMG0812 s prevleko (Ti, Al)N+TiN. Analizirani in predstavljeni so tudi mehanizmi obrabe orodja in rezalne sile, pri čemer je bila uporabljena metoda ANOVA (analiza variance). Z multiregresijsko analizo so bile dobljene empirične enačbe, ki določajo odvisnost med parametri obdelave ter obrabo boka orodja in rezalnimi silami. Rezultati eksperimentov so potrdili, da se z visokotlačnim dovodom hladilne tekočine v območje obdelave občutno zmanjša obraba bokov orodja in rezalne sile. Rezultati analize ANOVA tudi kažejo, da ima visokotlačno hlajenje signifikanten ugoden vpliv na življenjsko dobo orodja. Zlitina Inconel 718 za letalsko in vesoljsko industrijo spada med težko obdelovalne zlitine. Cilj študije je določitev obdelovalnosti Inconela 718 v pogojih visokotlačnega hlajenja. Odvisnosti med parametri obdelave in obrabo orodja je treba določiti pred obdelavo Inconela 718. Izvedeni so bili eksperimenti na osnovi ortogonalnega polja Taguchi L18 pri treh različnih rezalnih hitrostih, podajanjih in tlakih, ter pri dveh različnih globinah reza, pri čemer je bil vsak preizkus opravljen z novim rezalnim robom za enostavno primerljivost rezultatov. Ugotovljena je bila obraba stružilnega orodja iz karbidne trdine CNMG0812 s prevleko (Ti, Al)N+TiN v pogojih visokotlačnega hlajenja pri obdelavi zlitine Inconel 718. Med preizkusi so bile merjene komponente rezalne sile in obraba boka orodja. Opravljena je bila analiza variance rezultatov ANOVA. Za preučevanje odvisnosti med parametri procesa in odzivom pri obdelavi je bilo uporabljeno tudi regresijsko modeliranje. Iz dela je mogoče zaključiti naslednje: 1. Dovod hladilno/mazalne tekočine pod visokim tlakom na stik med orodjem in odrezkom zmanjša komponente rezalne sile zaradi mehanskega učinka visokotlačne hladilne tekočine. 2. Visokotlačno hlajenje izboljšuje in zagotavlja želeno lomljivost odrezkov, ki se izboljša s kakovostjo obdelane površine. 3. Obraba rezalnega orodja, zlasti bokov, se zmanjša z dovodom hladilne tekočine pod visokim tlakom na stik med orodjem in odrezkom. Razlog je v tem, da visokotlačno hlajenje zagotavlja boljše mazanje in hlajenje kot običajno hlajenje. Visokotlačni curek tudi skrajša kontaktno dolžino med orodjem in odrezkom ter tako pomaga podaljšati življenjsko dobo orodja. 4. Tehnika visokotlačnega dovoda hladilne tekočine podpira usmeritev k trajnostni proizvodnji s podaljšanjem življenjske dobe orodja in zmanjšanjem rezalnih sil, zlasti pri težavnih materialih, s čimer je dosežena boljša produktivnost in manjša poraba energije. 5. Za trajnostno usmeritev so na voljo tudi manj koncentrirane emulzije za obdelavo z visokotlačnim dovodom hladilne tekočine (na vodni osnovi), ki manj škodujejo zdravju in okolju. Pri tej študiji so bili izbrani omejeni pogoji rezalne hitrosti in podajanja. Prav tako je bila konstantna tudi globina reza. Obdelava Inconela 718 z visokotlačnim hlajenjem je nov postopek. V študiji so analizirani vplivi rezalnih parametrov ter ravni tlaka na obrabo orodja. Za trajnostno usmeritev so na voljo tudi manj koncentrirane emulzije za obdelavo z visokotlačnim dovodom hladilne tekočine (na vodni osnovi), ki manj škodujejo zdravju in okolju. Ključne besede: obdelava z visokotlačnim dovodom hladilne tekočine, ANOVA, Taguchi

*Naslov avtorja za dopisovanje: Univerza Süleymana Demirela, Tehniška fakulteta, Katedra za proizvodno strojništvo, 32260, Isparta, Turčija, oguzcolak@sdu.edu.tr

SI 139

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 140-142 Osebne objave

Doktorske disertacije, znanstvena magistrska dela, diplomske naloge

DOKTORSKE DISERTACIJE Na Fakulteti za strojništvo Univerze v Ljubljani so z uspehom obranili svojo doktorsko disertacijo: dne 11. oktobra 2012 Luis Miguel Cardoso VILHENA PEREIRA DA SILVA z naslovom: »Effect of surface texturing on coefficient of friction« (Vpliv obličenja pri kontaktnih površinah na koeficient trenja) (mentor: izr. prof. dr. Bojan Podgornik); Cilj predstavljenega raziskovalnega dela je določitev učinkovitost obnašanja kontaktnih površin v različnih režimih mazanja. To smo dosegli s kombinacijo eksperimentalnih triboloških raziskav, FEM simulacijo in dinamično analizo toka fluida. V skladu z FEM simulacijo, rezultati triboloških preizkusov kažejo, da v pogojih pomankljivega mazanja obličenje ovira drsno gibanje s čimer se poveča koeficient trenja. Le ob zelo majhni gostoti vdolbinic le-te kažejo pozitiven vpliv zadrževanja in dovoda maziva v kontakt. Največje izboljšanje v smislu znižanja koeficienta trenja dosežemo v pogojih hidrodinamičnega mazanja, kjer vpliv obličenja močno zavisi od toka fluida. Padec tlaka na izstopnem delu vdolbinic in pojav vrtincev privede do znižanja trenja v kontaktu; dne 18. oktobra 2012 Domen ŠERUGA z naslovom: »Napovedovanje dobe trajanja izdelka zaradi lezenja s posplošenim časovno-temperaturnim parametrom« (mentor: prof. dr. Matija Fajdiga, prof. dr. Marko Nagode); Doktorska raziskava obravnava napovedovanje dobe trajanja izdelka zaradi lezenja pri termomehanskem obremenjevanju. Metoda temelji na uporabi numerične simulacije napetostnodeformacijskega stanja obremenjenega izdelka in ob upoštevanju posplošenega časovno-temperaturnega parametra omogoča določitev dobe trajanja do kritične poškodbe zaradi lezenja. Z razvito metodo smo omogočili celovito napovedovanje dobe trajanja termomehansko obremenjenega izdelka. Zasnovali smo posplošen časovno-temperaturni parameter, ki združuje lastnosti osnovnih časovno-temperaturnih parametrov. Na obsežnem naboru preizkusov lezenja kovinskih gradiv smo pokazali, da uporabnost posplošenega parametra ni omejena samo na določena gradiva. Ugotovili smo, da lahko kljub okrnjenemu številu rezultatov standardnih preizkusov lezenja pri visokih temperaturah ali visokih napetostih dobimo zadovoljive sklepe o dobi trajanja pri višjih napetostih ali višjih temperaturah. Koeficienti razvitega SI 140

posplošenega časovno-temperaturnega parametra so enolično določljivi z uporabo hitrega, preprostega, robustnega in numerično stabilnega algoritma; dne 26. oktobra 2012 Samo SIMONČIČ z naslovom: »Krmiljenje procesa uporovnega točkovnega varjenja na osnovi strojnega vida« (mentor: doc. dr. Primož Podržaj); Signal pomika elektrod je eden izmed najpogosteje uporabljenih signalov pri procesu električnega uporovnega varjenja. Največja težava pri njegovi uporabi je dejstvo, da običajne metode merjenja vključujejo termične raztezke elektrod. Elegantna rešitev tega problema je uporaba strojnega vida. V delu je predstavljen algoritem na tej osnovi, ki kot prvi ne zahteva posebnih značilnosti elektrode. V delu so predstavljeni rezultati eksperimentov, kjer smo raziskovali povezavo med nosilnostjo zvara in parametri krivulje pomika elektrod. ZNANSTVENA MAGISTRSKA DELA Na Fakulteti za strojništvo Univerze v Ljubljani je z uspehom zagovarjal svoje magistrsko delo: dne 4. oktobra 2012 Blaž ČERNEVŠEK z naslovom: »Časi in stroški sočasnega osvajanja izdelka« (mentor: prof. dr. Marko Starbek). * Na Fakulteti za strojništvo Univerze v Mariboru sta z uspehom zagovarjala svoje magistrsko delo: dne 10. oktobra 2012 David KOLAR z naslovom: »Študij visokotemperaturne oksidacije nerjavnega jekla EN X12Cr13 z meritvijo električne upornosti« (mentor: prof. dr. Ivan Anžel). dne 10. oktobra 2012 Mario PIŠKOR z naslovom: »Uporaba orodij za doseganje vitke proizvodnje v podjetju Oprem-uređaji d.d.« (mentor: izr. prof. dr. Borut Buchmeister). DIPLOMIRALI SO Na Fakulteti za strojništvo Univerze v Ljubljani so pridobili naziv univerzitetni diplomirani inženir strojništva: dne 2. oktobra 2012: Primož BREJC z naslovom: »Parametrična analiza kavitacije na prototipni izvedbi naprave za

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)11, SI 140-142

čiščenje pitne vode« (mentor: prof. dr. Branko Širok, somentor: izr. prof. dr. Marko Hočevar); Matej HERTL z naslovom: »Sistem priprave komprimiranega zraka v farmacevtskem podjetju« (mentor: prof. dr. Branko Širok); Marko NEMANIČ z naslovom: »Analiza pretočnih uporov v hidrodinamičnem prenosniku moči« (mentor: izr. prof. dr. Mihael Sekavčnik); Marko PETERNELJ z naslovom: »Plavajoči mlin na Muri« (mentor: prof. dr. Branko Širok, prof. dr. Marko Nagode); dne 24. oktobra 2012: Erazem MIRTIČ z naslovom: »Numerična določitev porušitve kompozitnih materialov z upoštevanjem mikro-sestave na primeru aluminija, ojačanega s karbonskimi vlakni« (mentor: prof. dr. Igor Emri); Luka SADAR z naslovom: »Primerjava mehanskih lastnosti prekrovnih varjenih spojev« (mentor: prof. dr. Janez Grum); dne 29. oktobra 2012: Miha FINŽGAR z naslovom: »Analiza dinamike kašlja na izbranem vzorcu populacije« (mentor: prof. dr. Vincenc Butala, somentor: doc. dr. Matjaž Fležar); Tadej KOLMAN z naslovom: »Razvojno vrednotenje gredi alternatorja« (mentor: prof. dr. Marko Nagode); Aleš MODIC z naslovom: »Model toplotne prehodnosti vakuumskega izolacijskega panela« (mentor: prof. dr. Iztok Golobič); Matevž PINTAR z naslovom: »Interakcija plimskih elektrarn na mobilnem preizkuševališču« (mentor: prof. dr. Branko Širok, somentor: prof. dr. Marko Nagode); Marko SCORTEGAGNA z naslovom: »Razvoj in analiza trupa dvoročnega robota« (mentor: izr. prof. dr. Niko Herakovič, somentor: doc. dr. Leon Žlajpah); Doris ŠKRJANEC z naslovom: »Eksergijsko okoljska analiza sistemov energijske pretvorbe« (mentor: prof. dr. Iztok Golobič). * Na Fakulteti za strojništvo Univerze v Mariboru je pridobil naziv univerzitetni diplomirani inženir strojništva: dne 11. oktobra 2012: Denis BARTLMÄ z naslovom: »Nadgradnja in rekonstrukcija linije ohišij Miramondi« (mentor: izr. prof. dr. Karl Gotlih, somentor: izr. prof. dr. Aleš Hace). * Na Fakulteti za strojništvo Univerze v Ljubljani so pridobili naziv diplomirani inženir strojništva:

dne 17. oktobra 2012: Marko KVARTUH z naslovom: »Porazdelitev temperatur v zemljini pri delovanju toplotne črpalke zemlja/voda« (mentor: prof. dr. Alojz Poredoš); Mitja MLINAR z naslovom: »Mehanske lastnosti induktivno kaljene nodularne litine« (mentor: prof. dr. Janez Grum); Miha NOVAK z naslovom: »Vzpostavitev funkcionalnega bloka zračnega prostora Srednje Evrope« (mentor: viš. pred. mag. Aleksander Čičerov, somentor: izr. prof. dr. Tadej Kosel); Gašper TUMPEJ z naslovom: »Analiza terena v oklici Letališča Edvarda Rusjana Maribor kot priprava za karto radarskega vodenja zrakoplovov« (mentor: izr. prof. dr. Tadej Kosel, somentor: pred. Miha Šorn); dne 19. oktobra 2012: Uroš DROBNIČ z naslovom: »Reševanje reklamacij z uporabo metode 8D« (mentor: prof. dr. Mirko Soković); Aleksander KOLAR z naslovom: »Optimizacija toka materiala« (mentor: izr. prof. dr. Janez Kušar, somentor: prof. dr. Marko Starbek); Rok LEBEN z naslovom: »Določevanje koncentracije vonja z metodo dinamične olfaktometrije« (mentor: prof. dr. Vincenc Butala); Simon URBAS z naslovom: »Kinematika toka na linijskih distribucijskih elementih« (mentor: prof. dr. Branko Širok); David HRIBERNIK z naslovom: »Stroškovna analiza obdelave na eno in več vretenskem stroju« (mentor: prof. dr. Janez Kopač); Matej ZORC z naslovom: »Eksperimentalna analiza vpliva drsniškega bata na dinamično obnašanje hidravličnega in pnevmatičnega batnega ventila« (mentor: izr. prof. dr. Niko Herakovič); Gregor ŽUPIĆ z naslovom: »Sistem za sočasno proizvodnjo toplote in električne energije v industrijskem procesu« (mentor: izr. prof. dr. Mihael Sekavčnik). * Na Fakulteti za strojništvo Univerze v Mariboru so pridobili naziv diplomirani inženir strojništva: dne 25. oktobra 2012: Viktor CAR z naslovom: »Uporaba in optimiranje razreza pločevine s plazmo pri izdelavi posod« (mentor: izr. prof. dr. Ivan Pahole, somentor: doc. dr. Mirko Ficko); Darko IGREC z naslovom: »Razvoj hidravlične vpenjalne priprave za ohišje dvojnega vijačnega turbokompresorja« (mentorica: viš. pred. dr. Marina Novak, somentor: izr. prof. dr. Bojan Dolšak); Bojan MATAIČ z naslovom: »Vpenjalni elementi pri odrezavanju« (mentor: prof. dr. Franci Čuš, somentor: doc. dr. Uroš Župerl); SI 141

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Petar PEČEK z naslovom: »Optimizacija varjenja tlačne posode za metanolovo lužnico« (mentor: izr. prof. dr. Vladimir Gliha, somentor: doc. dr. Tomaž Vuherer); Kristijan PIŠEK z naslovom: »Tehnološka izboljšava rezkalnega stroja za potrebe orodjarstva« (mentor: prof. dr. Miran Brezočnik, somentor: asist. dr. Simon Brezovnik); Denis PLIBERŠEK z naslovom: »Optimizacija transporta kolobarjev v podjetju Impol d.d.« (mentor: doc. dr. Marjan Leber, somentor: izr. prof. dr. Borut Buchmeister); Bojan ROZE z naslovom: »Rekonstrukcija stenskih elementov bivalnih kontejnerjev v podjetju

SI 142

Arcont d.d.« (mentor: viš. pred. dr. Marina Novak, somentor: izr. prof. dr. Bojan Dolšak). * Na Fakulteti za strojništvo Univerze v Mariboru sta pridobila naziv diplomirani inženir strojništva (VS): dne 25. okotbra 2012: Damir DUKARIĆ z naslovom: »Načrtovanje manipulatorja v vmesnem skladišču avtomobilskih pnevmatik« (mentor: prof. dr. Iztok Potrč, somentor: izr. prof. dr. Tone Lerher); Stanko KOLARIČ z naslovom: »Pregled sodobnih CNC - strojev za upogibanje žice« (mentor: prof. dr. Miran Brezočnik, somentor: izr. prof. dr. Ivan Pahole).

Strojniški vestnik – Journal of Mechanical Engineering (SV-JME) Aim and Scope The international journal publishes original and (mini)review articles covering the concepts of materials science, mechanics, kinematics, thermodynamics, energy and environment, mechatronics and robotics, fluid mechanics, tribology, cybernetics, industrial engineering and structural analysis. The journal follows new trends and progress proven practice in the mechanical engineering and also in the closely related sciences as are electrical, civil and process engineering, medicine, microbiology, ecology, agriculture, transport systems, aviation, and others, thus creating a unique forum for interdisciplinary or multidisciplinary dialogue. The international conferences selected papers are welcome for publishing as a special issue of SV-JME with invited co-editor(s). Editor in Chief Vincenc Butala University of Ljubljana Faculty of Mechanical Engineering, Slovenia Technical Editor Pika Škraba University of Ljubljana Faculty of Mechanical Engineering, Slovenia Editorial Office University of Ljubljana (UL) Faculty of Mechanical Engineering SV-JME Aškerčeva 6, SI-1000 Ljubljana, Slovenia Phone: 386-(0)1-4771 137 Fax: 386-(0)1-2518 567 E-mail: info@sv-jme.eu, http://www.sv-jme.eu Print Tiskarna Knjigoveznica Radovljica, printed in 480 copies Founders and Publishers University of Ljubljana (UL) Faculty of Mechanical Engineering, Slovenia University of Maribor (UM) Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia

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58 (2012) 11

Chamber of Commerce and Industry of Slovenia Metal Processing Industry Association

Since 1955

Strojniški vestnik Journal of Mechanical Engineering

chining Performance of Inconel 718 under High Pressure

Journal of Mechanical Engineering - Strojniški vestnik

Popescu, Peter Mitrouchev: mbly Analysis and Modeling Techniques: A Review ong Liu, Congkun Ren, Aibaibu Abulimiti, Xiaojie Tian,

mal and Electromagnetic Analyses of Subsea Solenoid Valves Preventers Celent, Sonja Jozić: uence of Cutting Parameters on the Surface Roughness, ng Force in Face Milling in Off-Line Process Control

no. 11 2012 volume 58

year

Strojniški vestnik - Journal of Mechanical Engineering is also available on http://www.sv-jme.eu, where you access also to papers’ supplements, such as simulations, etc.

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58 (2012) 11

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Papers

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Journal of Mechanical Engineering - Strojniški vestnik

Contents

11 year 2012 volume 58 no.

Strojniški vestnik Journal of Mechanical Engineering