Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

被引:0
作者
Mahdi Hadhri
Abderazzak El Ouafi
Noureddine Barka
机构
[1] University of Quebec,Mathematics, Computer Science and Engineering Department
来源
Journal of Mechanical Science and Technology | 2017年 / 31卷
关键词
Superficial heat treatment; Laser surface transformation hardening; AISI 4340 steel; Hardness profile prediction; Finite element method; Artificial neural network; Design of experiments;
D O I
暂无
中图分类号
学科分类号
摘要
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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页码:615 / 623
页数:8
相关论文
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