Optimization in EDM of D2 Steel with Multiple Surface Roughness Characteristics Using Hybrid Taguchi Method

Abstract

The present study presents a multi-response optimization problem by applying Principal Component Analysis (PCA) combined with Taguchi method. The aim of the study is to evaluate the best process environment which could simultaneously fulfill multiple Surface Roughness characteristics. As traditional Taguchi method cannot solve a multi-objective optimization problem; to overcome this limitation, Principal component analysis has been coupled with Taguchi method. Taguchi method assumes that the quality characteristics should be uncorrelated or independent which is not always fulfilled in actual condition. PCA is applied to remove response correlation and to calculate independent (uncorrelated) quality indices known as principal components. These principal components combined with weighted principal component analysis (WPCA) are used to calculate overall quality index denoted as Multiresponse Performance Index (MPI). This investigation combines WPCA and Taguchi method for forecasting optimal setting. The predicted result by this method was validated through confirmatory test proving the efficacy of the process.