A STUDY ON OPTIMIZATION OF CENTERLESS GRINDING 3H13 STEEL

International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN (P): 2249–6890; ISSN (E): 2249–8001 Vol. 10, Issue 3, Jun 2020, 1777-1790 © TJPRC Pvt. Ltd.

A STUDY ON OPTIMIZATION OF CENTERLESS GRINDING 3H13 STEEL NGUYEN HONG SON1 & DO DUC TRUNG2* 1

Center of Mechanical Engineering, Hanoi University of Industry, , Cau Dien Street, Bac Tu Liem, Hanoi, Vietnam

2

Faculty of Mechanical Engineering, Hanoi University of Industry, Cau Dien Street, Bac Tu Liem, Hanoi, Vietnam

ABSTRACT Round component with the minimum value of surface roughness and roundness error is the goal of most of the fine machine processes. This paper presents the research on optimization of plunge centerless grinding process when grinding the 3H13 steel to achieve the minimum value of surface roughness and roundness errors. The input parameters are center height angle of the workpiece, longitudinal dressing feed-rate, plunge feed-rate and control wheel velocity.

Using the result of twenty-nine sets in central composite design matrix to show the two second orders of surface rounghness and roundness error models. The final goal of this work focuses on the determination of optimum centerless grinding above the parameters for the minimization of surface roughness (min:  0.8 µm) and roundness errors (min:  1.5 µm).

Received: Jun 04, 2020; Accepted: Jun 24, 2020; Published: Jun 30, 2020; Paper Id.: IJMPERDJUN2020163

1. INTRODUCTION Centerless grinding is widely used in industry for precision machining of cylindrical components because of its

Original Article

KEYWORDS: Plunge centerless grinding, 3H13 steel, Optimization, Surface roughness & Roundness error

high production rate, easy automation, and high accuracy. 3H13 steel (PN standard - Poland) is a common alloy steel that is usually used in mechanical engineering using centerless grinding process.

To improve the centerless grinding process, it is necessary to optimize surface roughness and roundness errors, the most critical quality constraints for the selection of grinding factors in process planning.

Researches on the optimization of centerless grinding process were published by many authors: Minimizing the surface roughness and roundness errors of workpiece by selecting the optimization levels of control wheel speed, feed rate and depth of cut [1]. Minimizing the roundness error of workpiece and carrying out the regression analysis to model an equation to average out roundness error [2]. Predicting the set-up conditions to analyze the dynamic and geometrical instabilities, making it possible to study the influence of different machine variables in stability of the process [3]. Minimizing the surface roughness by developing an empirical model for it [4]. Minimizing the lobing effect by developing a stability diagram for workpiece and thereby selecting the grinding parameters and having found out that the characteristic root distribution of the lobing loop is periodic [5].

Investigating the workpiece roundness based on process parameters by both simulation and experimental analysis and finding out that a slower worktable feed rate and a faster workpiece rotational speed result in better roundness error [6]. Minimizing the roundness error of workpiece by selecting the optimization levels of dressing feed, grinding feed, dwell time and cycle time [7]. Minimizing the roundness error of workpiece by selecting the optimization range of the center height angle [8]. Giving a method of how to select the optimal stable geometrical

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configuration in centerless grinding [9]. Giving an algorithm for providing the optimum set-up condition [10]., etc.

This paper presents the research on the optimization of plunge centerless grinding process when grinding the 3H13 steel to achieve the minimum value of surface roughness and roundness errors. The input parameters include center height angle of the workpiece, longitudinal dressing feed-rate, plunge feed-rate and control wheel velocity.

2. EXPERIMENT SYSTEM 2.1 Centerless Grinding Model Plunge centerless grinding model is illustrated in figure 1. The value of center height angle can be adjusted by the value of A. The relationship between center height angle and A in equation 1:

 A  Rct  H   A  Rct  H    arcsin    Rdm  Rct   Rdd  Rct 

  arcsin 

(1)

Where, H is the distance from the grinding wheel center, control wheel center to the bottom of the workrest blade.

2.2 Components The component material was the 3H13 steel (56HRC), applied to the serial production elements for diesel engine and attachments. The experimental component, was supported by specially made workrest blade with a 30 0 angle. The chemical composition of experimental component is in Table 1.

Figure 1: Plunge Centerless Grinding Model

Table 1: Chemical Composition of Experimental Component C Si Mn Cr S 0.44 1.12 1.05 12.00 0.008 2.3. Grinding wheels Using the Al2O3 grinding wheel of Hai

Duong Grinding Wheels Joint Stock Company,

Viet Nam,

Cn80.TB1.G.V1.500.150.305x35m/s.

Besides, the standard rubber bonded control wheel of 273 mm x 150 mm x 127 mm dimesions was employed.

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2.4. Experimantal Machine Tool The grinding experiments were conducted on a M1080B centerless grinder with H = 210 mm, shown in Fig 2.

Figure 2: Experimental Machine Tool 2.5. Measuring Equipment The surface roughness was measured by a Mitutoyo Surftest SJ-401 at 0.8 mm cutoff value. The roundness error was measured by a dial gage with a precision of 5/10.000. Each ground component was measured three times. The surface roughness and roundness error response, summarized in Table 2, are the average reading of three consecutive measurements.

3. EXPERIMENT MATRIX The experiment matrix was conducted under chatter free conditions to keep the grinding wheel speed (34 m/s), the grinding depth (0.05 mm), the depth of dressing (0.01 mm), the spark-out time (1 s) and the coolant flow constant.

In this work, using the central composite design with four input paremeters, their levels are presented in Table 2.

This experimental matrix with 29 sets; these sets include 16 single-replicated orthogonal factorial points, 8 axial points located and 5 centre points, shown in Table 3.

Table 2: Input parameters and theirs Levels Parameter Levels Input parameters Units Symbol -2 -1 0 1 Center height angle (degree) CHA 4 6 8 10 Dressing feed-rate (mm/min) DFR 100 200 300 400 In-feed speed (μm/s) IFS 2 6 10 14 Control wheel velocity (m/min) CWV 20 25 30 35

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2 12 500 18 40

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Table 3: Experimetal Matrix and Results Input parameters

Output parameters Surface Roundness roughness error (µm) (µm) 0.53 5.34

No.

CHA (degree)

DFR (mm/min)

IFS (μm/s)

CWV (m/min)

1

10

200

6

35

2

8

300

2

30

0.83

4.66

3

4

300

10

30

1.09

5.00

4

6

400

6

25

1.51

6.66

5

6

400

6

35

1.21

5.34

6

8

300

10

30

0.50

2.00

7

6

200

14

25

0.62

5.00

8

10

200

14

35

0.70

6.00

9

6

200

6

25

0.61

4.34

10

10

400

14

35

0.88

2.00

11

8

300

10

20

0.77

6.66

12

6

200

14

35

0.58

3.66

13

6

400

14

25

1.34

5.34

14

10

400

14

25

1.22

2.34

15

8

300

10

30

0.48

2.66

16

8

300

10

30

0.50

2.00

17

8

300

10

30

0.47

2.66

18

8

300

10

40

0.48

6.66

19

10

200

6

25

0.35

3.00

20

10

200

14

25

0.68

4.66

21

10

400

6

35

0.84

3.66

22

6

200

6

35

0.68

4.66

23

6

400

14

35

0.92

2.66

24

12

300

10

30

0.76

3.00

25

8

500

10

30

1.62

4.00

26

8

200

10

30

0.47

5.34

27

10

400

6

25

1.07

2.66

28

8

300

18

30

0.88

3.66

29

8

300

10

30

0.53

3.00

3. EFFECT OF INPUT PARAMETERS ON OUTPUT PARAMETERS 3.1. Effect of Input Parameters on Surface Roughness Figure 3 depicts the main effect on surface roughness. The interaction effect of input parameters on surface roughness are shown in Figs 4-9. In each of these graphs, two input parameters are varied while the third and fourth parameters are the help as its mid value. The graphs show that all of the input parameters have a significant effect on the surface roughness.

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Figure 3: Main Ffect of Input Parameters on Surface Roughness

Figure 4: Interaction effect of CHA and DFR on Surface Roughness.

Figure 5: Interaction effect of CHA and IFS on Surface Roughness

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Figure 6: Interaction effect of CHA and CWV on Surface Roughness

Figure 7: Interaction effect of DFR and IFS on Surface Roughness

Figure 8: Interaction effect of DFR and CWV on surface Roughness

Figure 9: Interaction Effect of IFS and CWV on Surface Roughness

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3.2 Effect of Input Parameters on Roundness Error Fig 10 depicts the main effect on roundness error. The interaction effect of input parameters on surface roughness are shown in Figs 11-16. In each of these graphs, two input parameters are varied while the third and fourth parameters are the help as its mid value. The graphs show that all of the input parameters have a significant effect on the roundness error.

Figure 10: Main Effect of Input Parameters on Roundness Error

Figure 11: Interaction Effect of CHA and DFR on Roundness Error

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Figure 12: Interaction effect of CHA and IFS on Roundness Error

Figure 13. Interaction Effect of CHA and CWV on Roundness Error

Figure 14: Interaction effect of DFR and IFS on Roundness Error

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Figure 15: Interaction Effect of DFR and CWV on Roundness Error

Figure 16. Interaction Effect of IFS and CWV on Roundness Error

4. REGRESSION MODELS The statistical analysis software Minitab 16 was used to determine the regression coefficients. The analysis for estimated regression coefficients for surface roughnes and roundness error quadratic models is shown in Tables 4 and 5 respectively.

The surface roughness and roundness error models was developed in the form of non-reduced final equation in terms of coded parameters.

Table 4: Estimated Regression Coefficients for Surface Roughness Quadratic Model

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Surface roughness = 0.67457 - 0.20125 * CHA + 0.61069 * DFR - 0.0225 * IFS - 0.23167 * CWV + 0.40494 * CHA2 + 0.32902 * DFR2 + 0.33494 * IFS2 + 0.10494 * CWV2 - 0.13875 * CHA * DFR + 0.31 *

(2)

CHA * IFS + 0.08 * CHA * CWV - 0.1275 * DFR * IFS - 0.285 * DFR * CWV - 0.125 * IFS * CWV

Table 5: Estimated Regression Coefficients for Roundness Error Quadratic Model

Roundness error = 2.62009 – 1.6675 * CHA – 0.02747 * DFR - 0.9975 * IFS - 0.43167 * CWV + 0.80013 * CHA2 + 0.91386 * DFR2 + 0.96013 * IFS2 + 3.45013 * CWV2 – 2.0025 * CHA * DFR + 1.17

(3)

* CHA * IFS + 2.34 * CHA * CWV – 1.4925 * DFR * IFS – 1.125 * DFR * CWV – 1.34 * IFS * CWV

5. OPTIMIZATION In the process of optimization, the goal is to minimize the surface roughness and the roundness error, which form the multi objective optimizatio problem. Minitab 16 software is used to optimize these objectives. The optimization graph and numerical values are shown in Figure 17 and Table 6 respectively.

Figure 17: Optimization Graph.

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A Study on Optimization of Centerless Grinding 3h13 Steel

Output parameters Surface roughness Roundness error

Objective function Min Min

1787

Table 6: Optimization Result Optimal Input Parameters CHA IFS DFR(mm/min) (degree) (μm/s) 11.8484

342.4242

6.8485

CVW (m/min) 27.0707

Predicted response 0.8079 1.5218

6. CONCLUSIONS For the work material 3H13 steel, all of four input parameters (CHA, DFR, IFS and CVW ) have a significant effect on both output parameters, surface roughness and roundness error. Thus, to achieve the minimum surface roughness and roundness error of the 3H13steel, the numerical values CHA, DFR, IFS and CVW

are 11.8484 (degree);

342.4242(mm/min); 6.8485 (μm/s) and 27.0707 (m/min) respectively.

REFERENCES 1.

Senthil Kumar N, Dhinakarraj C K, Deepanraj and Sankaranarayyanan G (2012) Multi Empirical Modeling of centerless Grinding Parameters.

Objective Optimization and

Emerging Trends in Science, Engineering and Technology

Lecture Notes in Mechanical Engineering 2012, pp 285-295.

2.

Naresh, E., et al. "Experimental Investigation on Friction Stir and Spot Welding of AA 6061 and Its Strength Measurements." International Journal of Mechanical and Production Engineering Research and Development 8.2 (2018): 1189-1200.

3.

Dhavlikar MN, Kulkarni MS, Mariappan V (2003) Combined Taguchi and dual response method for optimization of a centerless grinding operation. Int J Mater Process Technol 132:90–94.

4.

Garitaonandia I, Fernandes MH, Albizuri J, Hernandez JM, Barrenetxe D (2010) A new perspective on the stability study of centerless grinding process. Int J Mach Tools Manuf 50:165–173.

5.

Krajnik P, Kopac J, Sluga A (2005) Design of grinding factors based on response surface

methodology. Int J Mater

Process Technol 162–163:629–636.

6.

Shubhavardhan, R. N. "Microstructure and Tensile Strength of Friction Stir Welding of Al-Cu." International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) 5.2 (2015): 41-50.

7.

Zhou SS, Gartner JR, Howes TD (1996) On the relationship between setup parameters and lobing behavior in centerless grinding. Ann CIRP 45(1):341–346.

8.

Xu W, Wu Y, Sato T, Lin W (2010) Effects of process parameters on workpiece roundness in tangential-feed centerless grinding using a surface grinder. Int J Mater

9.

Process Technol 210:759–766.

PATEL, JAYG, and FALGUN PATEL. "TO STUDY AND OPTIMIZE THE PROCESS PARAMETER THROW ROLLER BURNISHING PROCESS ON EN19 MATERIAL."

International Journal of Mechanical Engineering (IJME) 5. 6, Oct–Nov

2016; 33-40 10. Khan ZA, Siddiquee AN and Kamaruddin S (2012) Optimization of In-feed Centerless Cylindrica; Process Parameters Using Grey Relational Analysis. Pertanika J Sci & Technol 20(2): 257 – 268 11. DUDHREJIA, MIHIR N., CHETAN B. BHATT, and MEHUL K. SHAH. "UNEXPLORED IDEA TO EXAMINE GRAIN SPECIMEN QUALITY BY UTILIZING IMAGE PROCESSING INTELLIGENCE." International Journal of Computer Science and Engineering (IJCSE) 6. 1, Dec - Jan 2017; 67-78

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12. Subramanya Udupa NG, Shunmagam MS and Radhakrishman V (1987) Optimizing workpiece position in centerless grinding by roundness profile analysis. Butter & Co

(Publishers) Ltd: 23-30

13. Chien AY (1984) The Selection of Optimal Stable Geometrical Configuration in Centerless Grinding. Int J. Mach Tool. Des. Res Vol 24 No 2: 87-93 14. Hashimoto F, Kanai A and Miyshita M (2004) Optimisation of Set-Up Conditions of the Centerless Grinding Process. Ann. CIRP 53 (1) 271-274

AUTHOR’S PROFILE

Ph.D. Nguyen Hong Son was born in 1978, in Ha Nam province, Viet Nam. He received the B.Sc., M.Sc. and Ph.D degrees from Hanoi University of Science and Technology, Vietnam in 2001, 2005 and 2015. He is currently a lecturer and researcher of Center for Mechanical Engineering, Hanoi University of Industry (HaUI).

Main Works •

Cutting process simulation

•

Cutting process optimization

•

Machining modeling

•

Machining prediction

•

Mechanical engineering

•

Elastic aerodynamics and numerical calculations

•

Software in Mechanical engineering

•

Design of Experiments (DOE)

Membership in Academic Societies •

Reviewer of Vietnam Journal of Science and Technology (VJST).

•

Reviewer of Vietnam Mechanics Association.

•

Reviewer of national journals and international journal of science

•

He authored/co-authored nearly 20 International Journal papers and International Conference papers.

Impact Factor (JCC): 8.8746

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Ph.D. Do Duc Trung was born in 1982, in Nam Dinh province, Viet Nam. He received the B.Sc., M.Sc. and Ph.D degrees from Thai Nguyen university of technology in 2005, 2010 and 2016.

Affiliation: Faculty of Mechanical Engineering, Hanoi University of Industry, Vietnam Address: No. 298, Cau Dien Street, Bac Tu Liem District, Hanoi City, Vietnam Brief Biographical History •

2005 - 2017: Faculty of Mechanical Engineering, Economic and Technical colleges Thai Nguyen, Vietnam. He was leader of mechanical engineering group.

•

2017 – present: Faculty of Mechanical Engineering, Hanoi University of Industry, Vietnam

Main Works: •

Cutting process simulation

•

Cutting process optimization

•

Software in Mechanical engineering

•

Design of Experiments (DOE)

Membership in Academic Societies •

Reviewer of Vietnam Journal of Science and Technology (VJST).

•

Reviewer of the ICERA 2018 & 2019 (International Conference on Engineering Research and Applications)

•

Member of Vietnam Mechanics Association.

•

Reviewer of national journals and international journal of science



He authored/co-authored nearly 40 International Journal papers and International Conference papers

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