Multi-objective particle swarm optimization of WEDM process parameters for inconel ۸۲۵

With the increased diversity of the customer demand and complexity of the product, Inconel ۸۲۵ 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 ۸۲۵. The wire electric discharge machining characteristics such as pulse-on time, pulse-off time, spark gap voltage, peak current, wire tension, wire feed are taken into consideration. The performance was measured in terms of material removal rate, surface roughness, and wire wear ratio. The central composite design of response surface methodology at an α value of ± ۲ was employed to establish the mathematical model between process parameters and performance measures. A multi-objective particle swarm optimization algorithm has been used to find the optimal solutions called Pareto optimal solutions. It uses the concept of dominance to find the non dominated set in the entire population and the crowding distance approach to finding the best Pareto optimal solutions with a good diversity of objectives. The confirmation experiments of the multi-objective particle swarm optimization algorithm show a significant improvement in material removal rate (۲۷.۹۳۴ to ۳۱.۶۸۷ mm۲/min), surface roughness (۲.۶۸۹ to ۲.۴۴۸μm), and wire wear ratio (۰.۰۲۷ to ۰.۰۳۰). SEM micrograph studies showed the number of cracks, pockmarks, craters, and pulled out material on the workpiece and wire electrode surface. Energy Dispersive X-ray analysis is performed to investigate the presence of elements on the work surface other than the base material.

Keywords:

WEDM , Inconel ۸۲۵ , surface roughness , Wire wear ratio , RSM , MOPSO algorithm