Optimization of EDM Process Parameters on Aluminum Alloy 6082 by Using Multi-objective Genetic Algorithm

Electric discharge machining is one of the most popular machines which are capable of machining geometrically complex and hard materials, that are precise and difficult to machine such as heat-treated tools, superalloys, heat-resistant steels, carbides, etc; these types of materials are being widely used in aerospace, automobiles, marine industries, etc. This paper aims to investigate the optimal set of process parameters of die sinker EDM on aluminum alloy 6082 with copper tube electrode by varying the input parameters such as pulse-on time (Ton), pulse-off time (Toff), current (I), and voltage (v). An L16 orthogonal array has been designed using the Taguchi method for input parameters to conduct experiments for getting the output variables such as metal removal rate (MRR) and tool wear rate (TWR). Based on the analysis, the experimental results have been carried out using ANOVA method. To find out the optimal set of values, multi-objective genetic algorithm (MOGA) is used to predict the experimental results. Upon comparing the experimental values and predicted values, an optimal value is obtained which is useful to the manufactures to get the high-performance rate of EDM to machine aluminum alloy 6082.