Multi-response optimization of the turn-assisted deep cold rolling process parameters for enhanced surface characteristics and residual stress of AISI 4140 steel shafts

Abstract

Surface and near-surface areas play an important role as far as safety and dependability of engineering components particularly when it is subjected to fatigue loading. By applying diverse mechanical surface enhancement (MSE) strategies, close to surface layers can be custom-made bringing about enhanced fatigue strength. MSE methods are used to generate surface hardened components without the time and energy-consuming heat treatment. Deep cold rolling (DCR) is one such method that can be employed where the mechanical energy induced enables surface-hardening of steels and thereby the combination of hardening and finishing in one single step. The objective of this work is to enhance residual stress and near-surface properties of AISI 4140 steel which is the most commonly used material in the automobile and aerospace industry. The samples were first turned and then deep cold rolled with various process parameters. Microstructure, surface hardness, surface finish, fatigue life, and residual compressive stress after the treatment were examined. Response surface methodology (RSM) and desirability function approach (DFA) was used to relate the empirical relationship between the various process variables and responses and also to determine the optimum parameter settings for better responses. Further, numerical simulation of turn-assisted deep cold rolling (TADCR) process was done by utilizing ANSYS-LS-DYNA software to understand the state of residual stress under various treating settings. Confirmation experiments conducted with the optimum parameter setting to validate the improvements in response and it is found that the deviation between optimum predicted and confirmatory experimental values is about 5%.