Machining parameter optimization for EDM machining of Mg-RE-Zn-Zr alloy using multi-objective Passing Vehicle Search algorithm

Mg alloys are known for their specific strength, stiffness, damping capacity, EMI shielding. Particularly, Rare earths added Mg alloys find applications in the gear box casing, transmission housing, engine mount, ribs, frames, instrument panels due to their improved corrosion resistance, pressure tightness, specific strength and creep strength. Reemergence of Mg alloys in the aircraft structural applications demands for advanced machining processes such as EDM to fabricate complex geometry parts. In this study, parametric multi-objective optimization of EDM on Mg-RE-Zn-Zr alloy is carried out using the novel meta-heuristic algorithm - Passing Vehicle Search (PVS). The input parameters considered are pulse-on (Ton), pulse-off (Toff) and peak current (A). Response surface method (RSM) is implemented through the Box-Behnken design to formulate a mathematical model for Material Removal Rate (MRR), Tool Wear Rate (TWR) and Roundness of holes. The accuracy of theoretical model has been established using the confirmation runs. Using the weighted sum method, the multi-objective PVS calculated optimal solutions for different weights to generate 2-D and surface pareto fronts. These pareto fronts were evaluated for performance determination of PVS using novel and established metrics such as spacing, spreading, hypervolume and pure diversity. The values of performance metrics indicate acceptable nature of the graphs and such analysis would facilitate better comparisons of solutions to select algorithms for optimization. Finally, decision making is illustrated with the help of level diagrams to draw up practical inferences for designing production plans and providing the best choice of machining parameters according to their preferences.