Coupled experimental-simulation approach with multi-strategy optimization in machining Nitronic-50 using MT-CVD inserts

Abstract

Dry-turning has been performed on Nitronic-50 with MT-CVD inserts by employing 3-factor, 3-level parametric combinations, in compliance with a face-centered CCD approach. Experimental outcomes include cutting force ( Fz ), tool-tip temperature ( TTT ), width of worn flank ( V B ), volumetric material removal rate ( VMRR ), and surface roughness ( Ra ) which were again compared against the corresponding simulated and response surface methodology-based predictive data. Wear dynamics is characterized by attrition, abrasion, crater, built-up-edge, and edge-chipping. Wear analysis through finite element method using Usui's wear criteria in DEFORM-3D software revealed influences of sliding velocity and contact stresses. Analysis of variance results denoted responses to be mostly impacted by turning velocity and depth of cut. Response surface methodology-driven predictive models and associated surface charts depict effective understanding of response behavior in relation to variable alterations. Additionally, machining metrics have been optimized utilizing multi-criteria decision-making and integrated multi-criteria decision-making-metaheuristics hybrid strategies. Post-optimization confirmation tests validated several improvements. Teaching–learning-based optimization-optimized parameters (100 m/minute turning velocity, 0.08 mm/rev feed, and 0.5 mm depth of cut) minimized Fz , TTT , V B , and Ra . MOORA and MOORA-teaching–learning-based optimization hybrid strategies maximized VMRR at 100 m/minute, 0.12 mm/rev feed, and 0.5 mm depth of cut.