Genetic Algorithm Based Optimization of ECDM Process for Polymer Matrix Composite

The acceptability of polymer matrix composites for various industrial applications has been increased over the years due to their better mechanical properties. However, nonconductive nature and fibrous residuals produced during micro drilling of these materials has become major challenge for the research fraternity. The conventional machining of these materials causes high tool wear due to presence of abrasive particles. Recently, the electrochemical discharge machining (ECDM) process has emerged as potential contender for the machining of nonconductive hard and brittle materials. Keeping in mind all these challenges, the present research work focuses on micro drilling of PMCs using ECDM process. The experimentation was planned as per Taguchi’s methodology using L9 orthogonal array. Voltage, electrolyte concentration and duty factor were considered as process parameters whereas material removal rate and taper were observed as output quality characteristics. The regression equation and coefficients were obtained using regression analysis. Using this regression equations, further solutions were obtained by genetic algorithm.