Particle Swarm Optimization of Wire Electrical Discharge Machining Parameters for NiTi Shape Memory Alloy

Abstract

Shape Memory Alloys (SMAs) find several applications in many fields such as Aerospace, Medical, Robotics and Automobile sectors because of its unique properties like super elasticity and shape memory effect. However, due to difficulty in machining of these SMAs, non-conventional methods such as Electric Discharge Machining (EDM), Wire EDM, Electro Chemical Machining (ECM), etc. are used instead of conventional methods. The specific applications of SMAs demand accurate dimensions and tolerances along with lower production cost. The input process parameters affect the accuracy and quality of machining of SMAs. The available optimization techniques such as Response Surface Method (RSM), Particle Swarm Optimization (PSO), Taguchi method, etc. can be used for finding the optimum value of input parameters. In the present work, PSO method is used to optimize the input parameters for machining of Nitinol–SMA using WEDM. The significant input parameters-Pulse on Time, Pulse off Time and Discharge current are considered in the present optimization study. The PSO results of input parameters are compared with that obtained by using response surface method. It is found that PSO method offers more accurate optimization of machining parameters as compared to RSM.