Analysis of Effect of Machining Parameters During Electrical Discharge Machining Using Taguchi-Based Multi-Objective PSO

Abstract

The present contribution describes an application of a hybrid approach using response surface methodology (RSM) and particle swarm optimization (PSO) for optimizing the machining parameters in electric discharge machining (EDM) of compo casted Al6061/ cenosphere AMCs. Compo casting processing route was employed to prepare the AMCs. Each experimentation in EDM was performed under different machining conditions of Peak Current (Amp), Pulse on time ([Formula: see text]s), and Flushing Pressure (bar). Performance characteristics such as material removal rates (MRRs), surface roughness (SR), and electrode wear rates (EWRs) were evaluated. A Taguchi L27 orthogonal array was considered to plan the experimentation and RSM was applied to model the inter relationship between the input process parameters and responses. A mathematic model has been developed to provide a fitness function to PSO by unifying the multiple responses. Finally, PSO was used to predict the optimal settings of the processing condition for the multi-performance optimization of the EDM operation. The experimental observations confirm the feasibility of the strategy and are in good accordance with the predicted value over a wide range of processing conditions employed in the process.