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 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 dif-ferent 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 form-ing quality is better than the other bending angle distribution methods.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

In this paper, a bending angle distribution function with optimized segmented boundary combination is proposed to improve the forming quality and reduce rebound defects in multi-pass roll forming. The stress and strain distributions in the sheets after each forming pass are analyzed using finite element simulation, and the influence of different bending angle parameters on sheet quality is obtained. The finite element simulation is verified by comparing experimental results.