Optimization of surface roughness and thickness of white layer in wire electrical discharge machining of DIN 1.4542 stainless steel using micro-genetic algorithm and signal to noise ratio techniques

Abstract

DIN 1.4542 alloy is one of the most important hardening stainless steel alloys used in the aerospace industries. Wire electrical discharge machining is a suitable process for accurate shaping and is used in situations where complex shapes or hard materials need to be machined. However, wire electrical discharge machining generates surfaces that have poor surface integrity properties, such as high surface roughness and white layer. Based on our knowledge and information, it has never been investigated so far. So, in this experimental research, effects of machining parameters, such as the power, time-off, voltage and servo and number of finish passes on the surface integrity (i.e. the surface roughness and maximum thickness of white layer) were investigated by using analysis of variance and regression analysis. Then the optimization of machining parameters was carried out using a signal-to-noise ratio and micro-genetic algorithm methods. Finally, confirmation tests were conducted to verify the performance of the optimization methods. From the results, significant effects of the discharge current and number of finish passes on the surface roughness and thickness of white layer can be seen. Based on the micro-genetic algorithm optimization method, a reduction of 52% and 67% in the surface roughness and thickness of white layer, respectively, is observed.