This paper describes an investigation on the optimization of process parameters on the Material Removal Rate (MRR) and kerf in Wire Electrical Discharge Machining (WEDM) operations. The experiments were carried out under varying pulse ON/OFF time, peak current, and wire feed by using Taguchi L9 orthogonal array. Grey Relational Analysis (GRA) optimization technique is used to find the optimal selection of process parameters for improvement in WEDM performance. The deviation of the kerf and material removal rate with process parameters is mathematically modeled by using Response Surface Methodology (RSM). The adequacy of the developed mathematical models is checked by Analysis of Variance (ANOVA). The problem is formulated as a multi-objective optimization as the influence of process input variables on material removal rate and kerf is conflicting in nature. Based on statistical analysis, it has been found that pulse on time, peak current is adequately influential parameters for MRR while pulse off time, peak current, and wire feed adequately influential for the kerf. Confirmation test result shows the application of the optimization technique for predicting optimal combinations of input variables for better output responses.

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WEDM process is newly emerged machining method in past decade which uses spark erosion method for the material removal while machining using high current. This method has shown high dimensional accuracy but gave rise to low machining rate. In current age of ultramodern technology a machine should satisfy more than one purpose. Therefore better Surface finish with dimensional accuracy for WEDM process has been very well presented in this paper with both the responses taken for study simultaneously. The paper deals with WEDM Process variables pulse ON/OFF time, peak current, servo voltage and wire feed rate. The paper also details about reduction of iterations for the desired output by using TLBO (Teaching-Learning Based Optimization) technique. The convergence graphs have been plotted in Minitab software to justify the reduction in iterations.

Much research has been devoted to improving manufactured

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