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

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 (mu 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.