Determination of optimal parameters with multi response characteristics of EDM by response surface methodology, grey relational analysis and principal component analysis

Abstract

This paper proposes a new combination of response surface methodology (RSM), grey relational analysis (GRA) and principal component analysis (PCA) modelling and optimisation method are used for the determination of the optimum process parameters that maximises material removal rate without compromising the surface quality in an AISI D2 tool steel. The input parameters of electrical discharge machining (EDM) considered for this analysis are pulse current ( Ip ), pulse duration ( Ton ), duty cycle ( Tau ) and discharge voltage ( V ). The effects of these parameters have been optimised by conducting by optimising multi response analysis. The designed experimental results are used in GRA, and the weights of the responses are determined by PCA. Based on optimisation results, using the RSM the interactive effects of the machining parameters on the responses were evaluated. It is found that the grey relational grade (GRG) was dominantly influenced by Ip and their interactions with the other parameters. This method is simple with easy operatability, the assessment outcome provides a scientific reference to obtain useful information about how to control the modelling parameter to ensure high productivity without compromising the quality of the EDM surfaces. The results have also been verified by running confirmation tests.