multi-objective particle swarm optimization of wedm process parameters for inconel 825

With the increased diversity of the customer demand and complexity of the product, inconel 825 is widely used to meet the actual needs, especially in the aerospace industry. it is difficult-to-cut material because of its high toughness and hardness. the present research attempts to optimize the process parameters of wire electric discharge machining during the cutting operation of inconel 825.the wire electric discharge machining characteristics such as pulse-ontime, pulse-off time, spark gap voltage, peak current, wire tension, wire feed aretaken into consideration. the performance was measured in terms of materialremoval rate, surface roughness, and wire wear ratio. the central compositedesign of response surface methodology at an α value of ± 2 was employed toestablish the mathematical model between process parameters and performancemeasures. a multi-objective particle swarm optimization algorithm has beenused to find the optimal solutions called pareto optimal solutions. it uses theconcept of dominance to find the non dominated set in the entire population andthe crowding distance approach to finding the best pareto optimal solutions witha good diversity of objectives. the confirmation experiments of the multi-objective particle swarm optimization algorithm show a significantimprovement in material removal rate (27.934 to 31.687 mm2/min), surfaceroughness (2.689 to 2.448μm), and wire wear ratio (0.027 to 0.030). semmicrograph studies showed the number of cracks, pockmarks, craters, andpulled out material on the workpiece and wire electrode surface. energydispersive x-ray analysis is performed to investigate the presence of elementson the work surface other than the base material.