Multi Response Optimization by Using the Hybrid Technique in Electro Discharge Machining of AISI 304

Abstract

Electro discharge machining (EDM) is most popular non-conventional electro-thermal machining process where electrical energy is used to generate a spark and thermal energy used to remove material from the workpiece. The primary goal of EDM is getting more material removal rate (MRR) with lower tool wear rate (TWR). For this investigation, machining parameters like peak current, pulse on time, gap voltage and duty cycle are considered as process parameter, and material removal rate (MRR) and tool wear rate (TWR) are considered as response. AISI 304 stainless steel and tungsten carbide are used as work material and tool material respectively. Taguchi L27 orthogonal array has been applied for designing the experiment. A hybrid optimization technique like desirability in combination with grey relational analysis (GRA) has been performed to get the optimum level of the control parameter for getting higher MRR and lower TWR. Analysis of variance (ANOVA) is performed for the statistical analysis. These results show that peak current is the most significant parameter for MRR and TWR. The optimal parameter setting for maximum MRR and minimum TWR has obtained by desirability coupled with Grey relational analysis.