Multi-criteria decision making with PCA in EDM of A2 tool steel

Abstract

In this investigation, experiments have been conducted with the help of full factorial design methodology in the Electro Discharge Machine (EDM) for machining of A2 tool steel. A cylindrical copper (99.9% pure) rod of 20 mm diameter has been selected as the electrode or tool material for machining. Four significant process parameters of EDM process such as discharge current (Ip), spark on time (Ton), duty cycle (Tau) and discharge voltage (V) have been studied in this research investigation. The effects of these parameters have been considered on the responses of EDM process such as Material Removal Rate (MRR) and Electrode Wear Rate (EWR) both in qualitative and quantitative terms. For qualitative analysis, main effect plots have been drawn, while for quantitative analysis ANOVA has been carried out. The significance of process parameters at 95% confidence interval has been found out through F-distribution and t-distribution values. ANOVA results revealed Ip and Ton as to be the major contributing process parameters for the considered EDM responses. Ip was found to have an 87.90% contribution towards MRR whereas Ton was having a 50.91% contribution towards TWR. Principal Component Analysis (PCA) has been implemented to find out the best trade-off between the responses MRR and EWR. The best process parameter setting for multi-criteria decision making among the answers such as MRR and EWR was found to be: Ip= 16A, Ton=500µs, Tau= 80%, V= 40volts.