Estimating the effect of process parameters on MRR, TWR and radial overcut of EDMed AISI D2 tool steel by RSM and GRA coupled with PCA

Abstract

This paper investigates an optimisation design of the various machining parameters for the electrical discharge machining (EDM) processes on AISI D2 tool steel using a hybrid optimisation method. A new combination of response surface methodology (RSM) and grey relational analysis coupled with principal component analysis (PCA) has been proposed to evaluate and estimate the effect of machining parameters on the responses. The major responses selected for this analysis are material removal rate, tool wear rate and radial overcut or gap, and the corresponding machining parameters considered for this study were pulse current (Ip), pulse duration (Ton), duty cycle (Tau) and discharge voltage (V). Thirty experiments were conducted on AISI D2 steel workpiece materials based on a face-centred central composite design. The experimental results obtained were used in grey relational analysis, and the weights of the responses were determined by the PCA and further evaluated using RSM. The results indicate that the grey relational grade (GRG) was significantly affected by the machining parameters considered and some of their interactions. The $R^2$ value for the GRG model was found to be 0.83, and the optimal parameter setting was determined for the grey relational grades. The analysis of variance results reveal that Tau is the most influencing parameter having 28.57 of percentage contribution followed by Ip, V and Ton with 11.52, 5.89 and 5.83 %, respectively. The interaction of the parameters contributes 31.19 % of percentage contribution. These results provide useful information on how to control the machining parameters and thereby responses and ensure high productivity and accuracy of the EDMed component. This method is simple with easy operability, and the results have also been verified by running confirmation tests.