Grey fuzzy multiobjective optimization of process parameters for dry electro discharge machining process

Abstract

Dry Electric discharge machining EDM process is an environmentally safe approach for the machining over the conventional oil-based EDM machining. Bright mild steel is difficult to machine due to its cold forging manufacturing process. The experiments were carried on bright mild steel with a hollow copper electrode which is having thin wall thickness as per the design of experiment using Taguchi method. In this study, the process parameters for the dry EDM are evaluated and optimized with two methods, grey relational analysis (GRA) and grey fuzzy logic respectively. The optimization has been carried out for the multiple response variables, material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) against the process variables. The process variables considered for this study are current, pulse on time (POT) and oxygen gas pressure. Also, the variance analysis has been carried out statically for all the process parameters against the response variables. Grey relational analysis (GRA) and Grey fuzzy multiobjective optimization was used to optimize level of process parameters. This paper also compared optimization results of GRA and grey fuzzy optimization process. It was observed that 15 A current, 100 POT and 2 bar dielectric pressure showed optimized results for better MRR, TWR and SR during machining of workpiece. Current and POT were significant process parameters for MRR and TWR.