Extensive evaluation of microhardness alterations induced in subsurface layers after hard machining of AISI 4340 steel and process optimization

ABSTRACT

Hardened AISI 4340 steel is extensively utilised in engineering industries. Owing to the fact that thermo-mechanical loads are applied to surface layers during the hard machining process, severe changes occur at the surface of the machined workpiece. These changes can affect some mechanical properties of the material, including microhardness, and residual stresses generation in material. Therefore, it is significantly influenced by process conditions and there is not any study in literature to extensively evaluate and optimise different indications of microhardness alteration after hard machining of AISI 4340 Steel. In this study, the influence of machining parameters was firstly studied on the microhardness distribution at machining of hardened AISI 4340 steel by experimental tests. Then, the optimal surface microhardness and depth of the affected layer were assessed using the intelligent techniques. In this regard, the optimal process conditions were simultaneously determined using the combination of the Artificial Neural Networks (ANNs) and Non-dominated Sorting Genetic Algorithm (NSGA-II). The results indicated that, both depth of the affected layer and surface microhardness were obtained in optimal state when the cutting speed changes from 720 to 600 (Rpm) and feed rate and depth of cut are 0.05 (mm/rev) and 0.4 (mm), respectively.

KEYWORDS:

• Hard machining
• microhardness
• artificial neural network
• multi objective optimization algorithm

Acknowledgments

This paper was extracted from the academic research project defined at Mahallat Institute of higher Education. The author would like to appreciate for support of the Institute.

Disclosure statement

No potential conflict of interest was reported by the author(s).