Abstract
The experimental study has been conducted on AISI 304 stainless steel in Electrical Discharge Machining (EDM) using Tungsten carbide electrode according to L27 orthogonal array. The main EDM input parameters name as pulse on time (P), discharge current (I), gap voltage (V) are chosen for exploring the effects on material removal rate (MRR) and surface roughness (SR). The main aim of this paper is to find out EDM optimum input parameters where the material removal rate (MRR) is maximized and while surface roughness (SR) is minimized. The regression model of MRR and SR was developed in statistical software using the experimental data. The developed regression models are optimized using two different optimization techniques namely Biogeography-Based Optimization (BBO) and Ant Colony Optimization (ACO).From these two optimization techniques, it has been observed that the BBO algorithm is more accurate than ACO. Finally a conformation test is performed to validate the BBO algorithm to obtain results and observed results showed satisfactory accuracy.
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