Investigation for obtaining the optimal solution for improving the performance of WEDM of super alloy Udimet-L605 using particle swarm optimization

The purpose of the current study is to increase the productivity, accuracy and reduce the cost of wire electric discharge machining of super alloy Udimet-L605. The pulse-on time, pulse-off time, peak current, wire tension, spark gap voltage, and wire feed rate have been considered as input variables in the experimental work on the wire electric discharge machining. The experimental work is planned on the basis of Taguchi's L27 orthogonal array and obtained the optimal combination of process variables for high cutting speed and lowest dimensional deviation and wire wear ratio, individually. The linear regression model is used to describe the interplay amid the input and output variables. After that, the PSO algorithm is applied to the developed model to obtain the global best solution for the desirable consequences of cutting speed, dimensional deviation and wire wear ratio. It has been observed that pulse-on time have a momentous effect on the cutting speed, dimensional deviation and wire wear ratio. The SEM and EDX are used to observe the erosion and compositional changes occurred during WEDM.