Abstract
This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process.
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Recommended by Associate Editor Sang-Hee Yoon
Mahdi Hadhri is a researcher student in the Department of Mathematics, Computer Science and Engineering at the University of Quebec at Rimouski. His research fields include manufacturing materials, manufacturing processes improvement, and quality management for industrial applications.
Abderrazak El Ouafi is a Professor in the Department of Mathematics, Computer Science and Engineering at the University of Quebec at Rimouski. He is also Director of Production and Automation Research Laboratory. His research interests are mainly oriented in precision engineering, manufacturing system design and control, improvement of manufacturing processes performance and intelligent control related to sensor fusion, neural networks and fuzzy control.
Noureddine Barka is an Assistant Professor in the Department of Mathematics, Computer Science and Engineering at the University of Quebec at Rimouski. His research fields include manufacturing materials, CAD/CAM, manufacturing processes improvement, and quality control for industrial applications.
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Hadhri, M., El Ouafi, A. & Barka, N. Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation. J Mech Sci Technol 31, 615–623 (2017). https://doi.org/10.1007/s12206-017-0114-4
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DOI: https://doi.org/10.1007/s12206-017-0114-4