Investigation of parameters and morphology of coated WC tool while machining X-750 using NSGA-II

Abstract

Abstract Nickel-based superalloys have numerous applications in automobile, aerospace, turbine blades, nuclear, oil refinery etc, due to their excellent properties like strength, wear resistance, corrosion resistance and higher creep strength. Because of these properties, modern manufacturing industries need help with the machining of nickel-based superalloys, i.e. hard-to-machine materials. In the present research, Ni-based X-750 alloy is machined with turning operation by a conventional lathe machine using a TiAlN PVD coated tungsten carbide tool at different rotational speed (TRS), depth of cut (DoC) and feed (F) values as input parameters whereas material removal rate (MRR) and tool wear (TW) are the responses of the study. The design of experiments (DoE) is prepared by response surface methodology-based Box-Behnken Design. Analysis of variance (ANOVA) was applied to investigate the percentage contribution of each machining parameter on responses. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) simultaneously optimizes the developed empirical models of MRR and TW. The predicted solutions suggested by NSGA-II are the best solution, and confirmation experiments are conducted on randomly selected parametric settings from these solutions. The optimized set presented by NSGA-II is TRS: 900RPM; DoC: 0.06 mm; F: 0.1 mm rev−1, and the maximum relative error in the case of MRR and TW is in the permissible limit. Scanning electron microscopy (SEM) and Energy dispersive spectroscopy (EDS) are used to investigate the morphology of tool insert before and after machining at optimized value TRS: 900 RPM; DoC: 0.1 mm; F: 0.06 mm rev−1, and it shows the wear marks on the tool, and the Energy dispersive spectroscopy confirms the presence of coating and WC. SEM is used to investigate the morphology of chips formed at different optimized parametric settings.