Multi-objective Parametric Optimization During WEDM of Silicon Through MOGWO

Abstract

Manufacturing industry into the photovoltaic market has paid more attention to the slicing of silicon ingot using advanced techniques with an increasing focus on an efficient and precise slicing method. Owing to the increasing energy demand due to the rising population, there is an increasing demand for sustainable energy recourse. Photovoltaic energy produced by the radiation of the sun is transformed into electricity with the help of photovoltaic cells, which use silicon wafers. Wire electro-discharge machining (WEDM) technology is used to slice the silicon wafer efficiently. In this study, a relatively new approach is used for parametric decision called multi-objective grey wolf optimizer (MOGWO) to make a better process parameter set in slicing the silicon ingot using WEDM. The experimental runs were performed using Taguchi L₂₇ orthogonal design, to study the influence of input parameters such as T_on, SV, OV, W_T, and T_off to evaluate the performance indicators. Regression analysis was used to create the mathematical prediction model for material removal rate and surface roughness. MOGWO was found to be an effective approach for multi-objective optimization as it provides improved results. Pulse on time 0.1 µs, servo voltage 38 V, open voltage 50 V, wire tension 1700 g and pulse off time 30 µs were the best parametric combinations for maximum material removal rate and minimum surface roughness.