Design Optimization for Cold Forging by an Integrated Methodology of CAD/FEM/ANN

被引:8
作者
Li, Suyang [1 ]
Cheng, Siyuan [1 ]
机构
[1] Guangdong Univ Technol, Fac Electromech Engn, Guangzhou, Guangdong, Peoples R China
来源
MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-5 | 2010年 / 97-101卷
关键词
Design optimization; Cold forging; CAE analysis; Artificial neural networks; Finite element method; NEURAL-NETWORKS; PREDICTION;
D O I
10.4028/www.scientific.net/AMR.97-101.3281
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, an integrated methodology of geometric modeling, finite element method (FEM) and artificial neural network (ANN) is proposed for design optimization of cold forging process. Forging processes with some key design variables are firstly simulated using rigid-plastic FEM so as to create training data for the ANN model. Then neural network model is used to predict for unseen data after being properly trained. Finally, some forging experiments are carried out to confirm the ANN prediction results, a good agreement is found between the predicted data and the measured results.
引用
收藏
页码:3281 / 3284
页数:4
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