RSM- and NSGA-II-Based Multiple Performance Characteristics Optimization of EDM Parameters for AISI 5160

In this paper, different methods of flushing are used to study the machining characteristics of electric discharge machining (EDM). Flushing mode plays an important role in any EDM operation. An incorrect flushing can result in erratic cutting and poor machining conditions. In present work, AISI 5160 alloy steel is selected as a work material to investigate the performance of EDM. Two of the most important response variables, surface roughness (SR) and material removal rate (MRR), are selected to compute the influence of input control factors. Central composite design is used for experimentation planning using response surface methodology. Analysis of variance is utilized to investigate the influence of control factors on response. Mathematical models are solved with the help of non-dominating sorting genetic algorithm II (NSGA-II). Validation experiments confirmed that at the optimal levels of process parameters the predicted values of MRR and SR were 1.167 g/min and 1.280 μ m , respectively. The predicted values of MRR and SR suggested by NSGA-II give a better correlation with experimental values, i.e., 1.149 g/min and 1.327 μ m , respectively.