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Erschienen in: The International Journal of Advanced Manufacturing Technology 9-10/2021

20.07.2021 | ORIGINAL ARTICLE

A prediction model for bending springback of AZM120 sheet metal and mechanical compensation of CNC automatic panel bender

verfasst von: Chen Chen, Junjie Gong, Yangdong Chen, Jinrong Wang

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 9-10/2021

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Abstract

Sheet springback and structural deformation of the folding mechanism are key issues in the sheet metal–forming process. Elastic-plastic bending theory and numerical simulation are applied to study the forming performance of sheet metal. First, a springback prediction model under general assumptions is established, based on the constitutive relationship of the elastic-plastic linear hardening material. In addition, the influences of processing parameters, such as sheet thickness and forming angle on springback, are analysed according to the theoretical model and verified by experiments. Then, a laser tracker is used to acquire the folding trajectory, and the structural deformation of the folding mechanism is confirmed by trajectory comparison. On this basis, numerical simulations are performed to collect deformation parameters, and a formula for mechanical compensation is obtained by linear fitting to the simulation data. Finally, experimental tests are carried out to verify the accuracy of the compensation model. The results show that the forming precision of the sheet metal can be controlled in the range of \(\pm 10^{\prime }\). The proposed method is generally applicable to linear hardening materials and operation conditions where the sheet thickness ranges from 0.8 to 3 mm.

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Metadaten
Titel
A prediction model for bending springback of AZM120 sheet metal and mechanical compensation of CNC automatic panel bender
verfasst von
Chen Chen
Junjie Gong
Yangdong Chen
Jinrong Wang
Publikationsdatum
20.07.2021
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 9-10/2021
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-021-07606-1

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