Modeling and optimization of EDM machined AZ-91 Mg alloy using ANFIS-VIKOR method

Abstract

In this paper, machining of AZ-91 magnesium alloy was performed in EDM using different tool electrode (Cu, CuW and graphite). To perform experiments, Taguchi L18 design of experiments was used to reduce experimental runs. EDM process parameters viz. polarity, current (Ip), pulse-on-time (Ton), pulse-off-time (Toff), and tool electrode material were considered in experimental design to measure the responses (MRR, Ra). Multi-input-single-output adaptive neuro fuzzy inference system (ANFIS) model was developed to predict responses, and predicted results were found in good agreement with the experimental results. Maximum MRR (0.089 g/min) was found at positive polarity, Ip-5 A, Ton-50 µs, Toff - 30 µs, and Cu tool, and minimum Ra (0.08 µm) was at parameters positive polarity, Ip-4 A, Ton-30 µs, Toff -20 µs, and Cu tool. Relative errors between experiential results and ANFIS predicted results were 1.17 % for MRR, and 2.20 % for Ra. Multi response optimization ANFIS-VIKOR method was successfully developed and gave compromise solution for MRR and Ra corresponding to minimum ANFIS-VIKOR index (Qi). A factor level analysis was performed to evaluate optimal factor combination for ANFIS-VIKOR index, and it shows that current (Ip) have a significant effect.