An experimental investigation and optimization of energy consumption and surface defects in wire cut electric discharge machining

Abstract

Optimizing the energy consumption and minimization of surface defects in wire cut electric discharge machining (WEDM) at the experimental design effectively saves energy and improves quality of machining. The present study is aimed to reduce energy consumption and improve machine performance related to kerf width, metal removal rate and surface quality in WEDM of Al-Si metal matrix composite. Current, pulse on time, pulse off time, voltage and wire tension are considered as controllable parameters and optimized using graph theory and utility concept (GTUC) and teaching learning based optimization (TLBO) algorithm considering criteria for the performance characteristics. It is observed that 26% of the additional energy is consumed in GTUC method while 40% less energy is consumed in TLBO method; the kerf width is found to be 8.4% more in GTUC and 2.8% less in TLBO respectively; the MRR is found to be 40.2% and 43.2% less in GTUC and TLBO methods respectively; 72.8% of the excess surface roughness is found in GTUC method while 1.2% less surface roughness is found in TLBO method. Effect of process parameters on the performance characteristics is also analyzed and the current is found to be dominant parameter. At TLBO optimized working condition, surface defects around kerf are found minimum.