Multi-performance characteristics optimization in near-dry rotary EDM of AlSiC by weighted principal component analysis

Abstract

In the current study, electrical discharge machining of particle reinforced aluminium matrix composite (AlSiC) using near-dry conditions is investigated. The investigation has been carried out by using de-ionized water as liquid phase and air as gaseous phase of a two-phase dielectric fluid. The gap between the work material and the tool is supplied with a little amount of de-ionized water droplets at a slow, steady pace using a minimum quantity lubrication (MQL) device. The process parameters included in the study are peak current, duty cycle, pulse-on time, tool rotation and air pressure. MRR (Material removal rate), TWR (Tool wear rate) and HT (Hole Taper) were selected as evaluation criteria. L27 (313) orthogonal array was used to conduct the experiments. The experimental results obtained were used in principal component analysis (PCA). The MPI (multi-response performance index), which combines these principal components and weighted principal component analysis (WPCA), is calculated as overall performance index. The approach is capable of forecasting optimal levels of machining factors. Significant factors and their contribution is determined by ANOVA performed for MPI. To validate the optimum parametric settings confirmatory experiment was conducted. Experimental results show that the responses in near dry rotary EDM process can be successfully improved using the suggested method.