Experimental and thermal investigation on die-sinking EDM using FEM and multi-objective optimization using WOA-CS

Abstract

This article proposes a numerical and experimental analysis of the effect of a die sinking electrical discharge machine (EDM) on a Nimonic C-263 workpiece with a copper-tungsten (Cu-w) electrode tool. Primarily, the finite element method (FEM) is employed to establish a two-dimensional (2-D) axisymmetric thermal model that utilizes several significant characteristics such as Gaussian heat distribution; distribution quantity of heat through the dielectric fluid, workpiece and tool; pulse on time (TON) and flushing efficacy. The model predicts the distribution profile of temperature on the workpiece during the process of die sinking EDM and obtains the material removal rate (MRR) from the temperature isotherm. An experimental analysis is performed to assess the accuracy of the results obtained from the numerical analysis, and the theoretically calculated MRR (T-MRR) is compared with the experimentally obtained MRR (E-MRR) for the effect of input process arguments such as gap voltage (VG), peak current (I), and TON. In addition, a quadratic polynomial regression model is proposed for output responses and the accuracy is checked by means of variance analysis. However, selecting the optimal combination of input process arguments is quite challenging and essential to being able to enhance the performance of the machining process. Thus, a multi-objective optimization using hybrid whale optimization with the cuckoo search algorithm (named as WOA-CS) is also proposed to find an enhanced machining performance with higher MRR values, a lower tool wear rate (TWR), and a lower surface roughness (SR). Finally, validation of these obtained optimal values is carried out with respect to the experimental results in order to prove the significance of the proposed WOA-CS algorithm in terms of relative error.