Parametric Optimization of Wire – EDM by Using Fuzzy Logic

ISSN 2320 – 6020

IJBSTR RESEARCH PAPER VOL 1 [ISSUE 8] AUGUST 2013

Parametric Optimization of Wire – EDM by Using Fuzzy Logic Rajneesh Kumar Singh1, D. K.Singh2 and Vivek Kumar3 ABSTRACT- The objective of present work is to stimulate the machining of material by WIRE electrical discharge machining (WEDM) to give effect of input parameters like pulse on time (Ton), pulse off time (T off), tension(T) and flushing rate(FR) which can bring about changes in the output parameter, i.e. cutting rate, material removal rate and surface roughness. Experimental data was gathered from WEDM using Brass wire electrode and Die steel skd 61 as work-piece. The rules of membership function (MF) and the degree of closeness to the optimum value of the Cutting rate, MMR and Ra are within the upper and lower range of the process parameters. It was found that proposed fuzzy model is in close agreement with the experimental results. By Intelligent, model based design and control of WEDM process parameters in this study will help to enable dramatically decreased product and process development cycle times.

KEY WORDS: Wire Electrical discharge Machining (WEDM), Fuzzy Logic, Membership functions (MF).

1. INTRODUCTION Additional the development of mechanical industry, the demands for alloy materials having high hardness, toughness and impact resistance are increasing. However, such materials are difficult to be machined by traditional machining methods.

Hence, non-traditional machining methods including electrochemical machining, ultrasonic machining, electrical discharging machine (EDM) etc. are applied to machine such difficult to machine materials. WEDM process with a thin wire as an electrode transforms electrical energy to thermal energy for cutting materials. With this process, alloy steel, conductive ceramics and aerospace materials can be machined irrespective to their hardness and toughness. Furthermore, WEDM is capable of producing a fine, precise, corrosion and wear resistant surface [1]. WEDM is considered as a unique adoption of the conventional EDM process, which uses an electrode to initialize the sparking process. However, WEDM utilizes a continuously travelling wire electrode made of thin copper, brass or tungsten of diameter 0.05-0.30 mm, which is capable of achieving very small corner radii. The wire is kept in tension using a mechanical tensioning device reducing the tendency of producing inaccurate parts. During the WEDM process, the material is eroded ahead of the wire and there is no direct contact between the work piece and the wire, eliminating the mechanical stresses during machining.

1

Author: Rajneesh Kumar Singh is currently pursuing Master of Technology program in Computer Integrated Manufacturing, MMM Engineering College, Gorakhpur, UP, India, PH-9918985312.

E-mail: rajneesh.srmcem@gmail.com 2 Co-Author: D. K. Singh is currently Professor & Head in Mechanical Department in MMM Engineering College, Gorakhpur, UP, India. E-mail: _dhirenks@mail.com 3 Co-Auther: Vivek Kumar is currently pursuing Master Of Technology Program In Computer Integrated Manufacturing, MMM Engineering College, Gorakhpur, UP, India.

Several researchers have attempted to improve the performance characteristics namely the surface roughness, cutting speed, dimensional accuracy and material removal rate etc. Puri and Bhattacharyya [2] employed Taguchi methodology involving alloy (Ti-6Al-4V) and used a datamining technique to study the effect of various input parameters of WEDM process on the cutting speed and Ra. They reformulated the WEDM domain as a classification problem to identify the important decision parameters. In their approach, however, the optimal process parameters for the multiple responses need to be decided by the engineers based on judgment. Kuriakose et. al. [3] carried out experiments with titanium and material removal rate (MRR) in wire electrical discharge machining (WEDM) operations. Based on ANOVA method, the highly effective parameters on both the Surface roughness and the MRR were found as open circuit voltage and pulse duration, whereas wire speed and dielectric flushing pressure were less effective factors. Optimization of the machining process first requires a mathematical model to be established to correlate the desired response and the process control parameters. Thereafter an optimization technique is applied to find optimal setting of the control parameters to derive the desired responses. Mukherjee and Ray [4] presented a generic framework for parameter Optimization in metal cutting processes for selection of an appropriate approach.

Response Surface Methodology (RSM) is generally employed to design experiments with a reduced number of experimental runs to achieve optimum responses. Lalwani et. al. [5] applied RSM to investigate the effect of cutting parameters on surface roughness in finish hard turning of MDN250steel using coated ceramic tool. Fuzzy logic had also been used by Rajyalakshmi G. [6] for the optimization of WEDM and investigated it effect on surface roughness. Fuzzy logic is one of the artificial intelligence techniques having ability to tackle the complex problem of complex relations among variables that cannot be accomplished by traditional methods. Fuzzy logic is a form of many- valued logic; it deals with reasoning that is fixed or

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IJBSTR RESEARCH PAPER VOL 1 [ISSUE 8] AUGUST 2013 appropriate rather than fixed and exact. In contrast with “crisp logic”, where binary sets have two-valued logic; true or false, fuzzy logic variables may have a truth value that ranges in degree between 0 and 1. The Mamdani implication method is employed for fuzzy inference reasoning in this paper.

SELECTION OF PROCESS PARAMETERS

2. PRINCIPLE WORKING OF WEDM The WEDM machine tool comprises of a main worktable (XY) on which the work piece is clamped; an auxiliary table (UV) and wire drive mechanism. The main table moves along X and Y-axis and it is driven by the D.C servo motors. The travelling wire is continuously fed from wire feed spool and collected on take up spool which moves though the work piece and is supported under tension between a pair of wire guides located at the opposite sides of the work piece. A series of electrical pulses generated by the pulse generator unit is applied between the work piece and the travelling wire electrode, to cause the electro erosion of the work piece material. While the machining operation is continuous, the machining zone is continuously flushed with water passing through the nozzle on both sides of work piece. Since water is used as a dielectric medium, it is very important that water does not ionize. Therefore, in order to prevent the ionization of water, an ion exchange resin is used in the dielectric distribution system to maintain the conductivity of water.

Fig 1. Schematic Diagram of the Basic Principle of WEDM Process (International Journal of Scientific Engineering and Technology Volume No.2, Issue No.6, pp : 600-606) 3. EXPERIMENAL SET UP. Experiments have been performed on five axis CNC Wire cut EDM (Fanuc robocut α-1iE) at MSME Indo Danish Tool Room, Jamshedpur, and Jharkhand. (India). The WEDM machine tool has the following specifications:

PULSE ON TIME The pulse on time is referred as Ton and it represents the duration of time in micro seconds, μs, for which the current is flowing in each cycle.

PULSE OFF TIME The pulse off time is referred as T off and it represents the duration of time in micro seconds, μs, between the two simultaneous sparks.

WIRE TENSION Wire tension determines how much the wire is to be stretched between upper and lower wire guides.

FLUSHING PRESSURE Flushing Pressure is for selection of flushing input pressure of the dielectric. The flushing pressure range on this machine is 0-7.

WORK PIECE MATERIAL The Skd 61 alloy steel plate of 100mm x 50mm x 7.5mm size has been used as a work piece material for the present experiments. Skd 61 is special hot-worked chromium toolsteel with good hardness and toughness properties. It is used for extreme load conditions such as hot-work forging, extrusion etc.

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IJBSTR RESEARCH PAPER VOL 1 [ISSUE 8] AUGUST 2013

for each input variable (pulse on time, pulse off time, tension, and flushing rate) as shown in fig 3.

(a)

(b)

4. FUZZY LOGIC MODEL FOR WIRE-EDM The modelling of wedm has been done using fuzzy interface system (fis). In this study, three angular membership functions are selected for fuzzy model (c)

Fig.2: Fuzzy logic model This step is to define linguistic value assigned to the variables by fuzzy sub-sets and their associated membership functions which may be zero or one called the grades of membership.

Zero membership value indicated that it is not a member of the fuzzy-set & one represents a complete member. A membership function can have any shape but preferably should be symmetric which includes, trapezoidal, triangular and bell shaped. Three membership functions were generated

(d) Fig 3: Membership function for input parameters (a) T on, (b) T off, (c) Tension and (d) Flushing rate Membership functions for cutting rate, MMR and surface roughness as output variables of the material is shown in fig .4

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(a)

Fig. 5 Formulation of Rules The set of rules along with membership function is shown in rule viewer of fuzzy model (Fig. 6). Fig. 6 reveals that after the formulation of rules, the optimum value of cutting rate material removal rate and surface roughness at any setting between the low and high limits of the process parameter can be predicted.

(b)

(c) Fig. 4 Membership Functions for Output Parameters.(a) cutting rate ,(b) MMR and (c) surface roughness

Fig. 6 Rule Viewer of Fuzzy Model

For obtaining optimized solution, the rules at the base have been defined correctly and these rules were written based upon the experimental results. While preparing the rules, fuzzy method was used. Some selected rules are reported in Fig. 5, using MATLAB 7.9.0 environment using Mamdani-type of fuzzy inference system in fuzzy logic toolbox.

Fig. 6 clearly shows that at pulse on time 13 μs and pulse off time 68 μs, tension 1728and flushing 12 predicts optimum value of Cutting rate as 1.69 mm/min, MRR as 12.2 mm3/min.

Similarly, for different sets of data points in the identified universe of discourse of undertaken parameters various other values of MRR in electrical discharge machining process can be predicted from the fuzzy model.

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IJBSTR RESEARCH PAPER VOL 1 [ISSUE 8] AUGUST 2013

to be 12.69 %for cutting rate, for MMR it is 16.36%and for surface roughness is17.87%. Thus the system gave an overall 75% accuracy from fuzzy model. Hence can be act as an alternative to conventional modelling method.

CONCLUSION • The operation of fuzzy logic to evaluate the response of the output parameter i.e. Cutting Rate, MRR and Surface Roughness has been emphasized in this paper. After comparison between the experimental values and the values generated by fuzzy operation were found to be interrelated with accuracy of 75%.

• During the research the fuzzy logic system was found to be more simple to evaluate and responsive than experimental models.

• Present study favors that the fuzzy logic technique can be introduced as a practicable technique to carry out analysis without conducting actual experiments.

REFERENCES 1.

2.

Fig. 7 Control surfaces of Fuzzy model Control surface as shown in fig .7 give the interdependency of input and output parameters guided by the various rules in the given universe of discourse for the same.

3.

4.

5. RESULTS AND DISCUSSION Table 4 gives the comparison of the predicted responses using 5.

6.

fuzzy model and conducted experimental data. There seems to be a good agreement between fuzzy model and experimental values in all cases. In the present study the random 5 data points were taken and the closest value that of various responses predicted from fuzzy experimental model was found

Gokler, M. I., Ozanozgu A. M. (2000), “Experimental investigation of effects of cutting parameters on surface roughness in the WEDM process”, International Journal of Machine Tools & Manufacture, 40, 1831–1848.

Puri, A. B. and Bhattacharyya B. (2003), “Modeling and analysis of the wire-tool vibration in wire-cut EDM”, Journal of Materials Processing Technology, 141, 295–301.

Kuriakose. S., Shunmugam, M. S. (2004), “Characteristics of wire-electro discharge machined Ti6Al4V surface”, Materials Letters, 58, 2231– 2237.

Mukherjee, I and Ray, P.K, “A review of optimization techniques in metal cutting processes”, Computers& Industrial Engineering, Vol. 50, 2006, pp. 15-34.

D.I. Lalwani, N.K. Mehta, P.K. Jain, “Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel,” Journal of materials processing technology, vol.206, 2008, pp.167–179.

Rajyalakshmi.

G, Venkatan Ramaiah P., “Optimization of Process Parameters of Wire Electrical Discharge Machining Using Fuzzy logic Integrated with Taguchi Method”, International Journal of Scientific Engineering and Technology (ISSN: 2277-1581) Volume No.2, Issue No.6, pp : 600-606

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