Process parameter optimization during EDM of AISI 316 LN stainless steel by using fuzzy based multi-objective PSO

The present contribution describes an application of a hybrid approach using fuzzy logic and particle swarm optimization (PSO) for optimizing the process parameters in the electric discharge machining (EDM) of AISI 316LN Stainless Steel. In this study, each experimentation was performed under different machining conditions of pulse current, pulse on-time, and pulse off-time. Machining performances such as MRR and EWR were evaluated. A Taguchi L9 orthogonal array was produced to plan the experimentation and the regression method was applied to model the relationship between the input factors and responses. A fuzzy model was employed to provide a fitness function to PSO by unifying the multiple responses. Finally, PSO was used to predict the optimal process parametric settings for the multi-performance optimization of the EDM operation. The experimental results confirm the feasibility of the strategy and are in good agreement with the predicted results over a wide range of machining conditions employed in the process.