Development of Mathematical Model for Predicting the Electric Erosion Behavior of TiO2 Filled Al-Zn-Mg-Cu (AA7075) Alloy Composite Using RSM-DFA Method

Abstract

This work aims to develop a mathematical model and predict the machining performance characteristics of electric discharge machining (EDM) process using response surface methodology (RSM) coupled with desirability function approach (DFA). The effect of various factors, such as electrode material, pulse current, pulse ON time and pulse OFF time were selected as input process parameters with an objective to maximize the material removal rate (MRR), minimize the surface roughness (SR) and electrode wear ratio (EWR). The machining was conducted on Al-Zn-Mg-Cu (AA7075) alloy composite reinforced with 10[Formula: see text]wt.% TiO2 particulates produced by stir casting route. The experimental work was planned as per L27 orthogonal array using design of experiments through RSM. Experimental results show that, pulse current and pulse ON time are the most significant factors for MRR and SR while electrode materials and pulse current have notable effect on EWR. Finally, multi-response optimization was performed to predict the EDM parameters by using DFA. The optimum combination of parameters were identified as electrode material (Br), pulse current (15 amps), pulse ON time (900[Formula: see text][Formula: see text]s) and pulse OFF time (30[Formula: see text][Formula: see text]s).