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Automatic and robust design for multiple self-piercing riveted joints using deep neural network
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Zhao, Huan, Han, Li, Liu, Yunpeng and Liu, Xianping (2022) Automatic and robust design for multiple self-piercing riveted joints using deep neural network. International Journal of Advanced Manufacturing Technology . doi:10.1007/s00170-022-09893-8 ISSN 0268-3768.
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Official URL: http://dx.doi.org/10.1007/s00170-022-09893-8
Abstract
Self-piercing riveting (SPR) is one of the major joining processes in the automotive industry. However, the frequently used design method for multiple SPR joints is still time-consuming, and relies heavily on engineers’ experience and experimental SPR tests. This research focuses on simplifying the joint design process and improving the design robustness for multiple SPR joints. A fast joint quality prediction model was firstly developed using the deep neural network (DNN), and verified through experimental SPR tests. Then, a joint robustness evaluation strategy was proposed by combining the developed DNN with the Monte Carlo method to consider the manufacturing tolerances of rivet, sheets, and die. Afterwards, two novel approaches were developed to quickly identify the suitable joint design with minimum rivet/die combinations for multiple sheet combinations. The first approach realizes automatic design of robust joints with the DNN model, the robustness evaluation method, and a proposed automatic selection algorithm. The second approach was developed based on application range maps of potential rivet/die combinations, and can be used to quickly identify the suitable joint design for multiple sheet combinations. Finally, experimental SPR tests were conducted to validate the effectiveness of the two joint design methods. Results from this study are helpful to simplify the design process, shorten the design cycle, and improve the robustness of multiple SPR joints.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Journal or Publication Title: | International Journal of Advanced Manufacturing Technology | ||||||||
Publisher: | Springer UK | ||||||||
ISSN: | 0268-3768 | ||||||||
Official Date: | 2022 | ||||||||
Dates: |
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DOI: | 10.1007/s00170-022-09893-8 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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