Sensitivity analysis and optimization of EDM process parameters

Electrical discharge machining (EDM) is a broadly used nonconventional material removal process for the machining of conductive work material irrespective of their hardness. In this article, empirical models for material removal rate (MRR) and surface roughness (R_a) of the workpiece are developed based on the extensive experiments performed on a special steel (WP7V) workpiece using a copper electrode. To account for the various parameters, an experimental design based on response surface methodology (RSM) is conducted considering three different factors namely-current, pulse-on-time, and pulse-off-time, each having three different levels. Analysis of variance (ANOVA) is conducted to test the statistical significance of the proposed empirical models. It is essential to determine the relationship and significance of input-output variation. Thus a sensitivity analysis is conducted. The interaction effect of input variables is also studied. Two different state-of-art optimization techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO), are applied to predict the optimal combination of process parameters. Finally, multi-objective optimization is also carried out to simultaneously maximize MRR while minimizing R_a.