Rebound control in multipass roll forming of cap-shaped parts based on segmental boundary optimization function

Bending angle is an important parameter in multi-pass roll forming. However, in actual manufacturing, there is still a lack of theoretical guidance; hence, rebound defects are commonly observed. In this paper, a bending angle distribution function with an optimized segmented boundary combination is...

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Bibliographic Details
Main Authors: Chunjian Su, Xuemeng Li, Zhengyang Feng, Xinxin Li, BalasundaramSelvanNaveen, Luhua Zhao, Weimin Huang
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Materials & Design
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Online Access:http://www.sciencedirect.com/science/article/pii/S0264127522011352
Description
Summary:Bending angle is an important parameter in multi-pass roll forming. However, in actual manufacturing, there is still a lack of theoretical guidance; hence, rebound defects are commonly observed. In this paper, a bending angle distribution function with an optimized segmented boundary combination is proposed to improve the forming quality and reduce the rebound defects in multi-pass roll forming. For cap-shaped sheets, COPRA, a roll-bending simulation software, is used to investigate the bending angle distribution to optimize the process of cap-shaped roll-bending. Furthermore, the stress and strain distributions in the sheets after each forming pass is analyzed using finite element simulation. The influence law of different bending angle parameters on the quality of sheets is obtained. The finite element simulation is verified by comparing the experimental results of the change law of rebound defects of cap-shaped parts under different bending angle distribution conditions. Based on the segmented boundary combination of bending angle optimization functions, the stress and strain distributions in the sheets during roll-bending forming of the cap-shaped parts are improved, the rebound defects in the bending area are smaller, and the forming quality is better than the other bending angle distribution methods.
ISSN:0264-1275