Optimization and Prediction of White Layer Thickness After Hard Turning

Turning hard steels is part of high-speed machining. This machining technique is characterized by cutting conditions four to ten times superior to conventional machining. High-strength materials have superior mechanical and physical characteristics to most conventional materials. With a very high hardness of 50/62HRC after heat treatment, they are used in various industrial applications such as engine components, shafts, ball bearings, etc. These critical parts are often subjected to very high thermal and mechanical loads, which can lead to micro-structure/phase changes such as the formation of a white layer. Machining these parts has an impact on their service life and on the integrity of the machined surfaces in terms of deformation, residual stresses, microstructure and subsurface damage which influence fatigue life. An in-depth study of white layer formation during hard machining of steels is proposed, focusing on chemical composition and the effects of machining conditions. AISI 52100 and AISI 4340 steels were considered in this study. Firstly, a single-objective optimization algorithm is used to determine the optimum by maximizing white layer formation. Secondly, a neural network-based model is developed to predict white layer thickness during hard turning of the steels.