Simultaneous optimization of multi performance characteristics in dry turning of Inconel 718 using NSGA-II

The conventional methods of optimization are unable to handle non differentiable or discontinues functions. Evolutionary Algorithms (EA) are efficient in handling non differential or discontinues functions. Non Dominated Sorting Genetic AlgorithmII (NSGA-II) is an efficient method for solving Multi-Objective optimization problems. Super alloy Inconel 718 is a high temperature alloy capable of having high creep rupture strength at high temperatures to about 650 degrees C to 750 degrees C. It is a difficult to cut material and is widely used in manufacturing of aircraft parts such as turbine disks, turbine blades, etc. A Multi Objective Optimization technique, NSGA-II has been used to predict the optimum values of process variables (Cutting speed, Depth of cut and Feed-rate) in high speed dry turning of Inconel 718 with PVD coated carbide tool by considering Material Removal Rate and Surface Roughness as Multi performance characteristics. According to NSGA-II's Pareto Optimal solutions, the best MRR obtained was 7462.42 mm3/ min and the best surface roughness was found to be 0.375 mu m. (C) 2015 Elsevier Ltd. All rights reserved.