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Updated: Mar 22, 2026

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
Published on: December 13, 2016
Development of a Prediction Model Based on RBF Neural Network for Sheet Metal Fixture Locating Layout Design and
Zhongqi Wang1, Bo Yang1, Yonggang Kang1
1The Ministry of Education Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, No. 127, Youyi Road (West), Xi'an 710072, China.
Abstract:
Fixture plays an important part in constraining excessive sheet metal part deformation at machining, assembly, and measuring stages during the whole manufacturing process. However, it is still a difficult and nontrivial task to design and optimize sheet metal fixture locating layout at present because there is always no direct and explicit expression describing sheet metal fixture locating layout and responding deformation. To that end, an RBF neural network prediction model is proposed in this paper to assist design and optimization of sheet metal fixture locating layout. The RBF neural network model is constructed by training data set selected by uniform sampling and finite element simulation analysis. Finally, a case study is conducted to verify the proposed method.
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