Image-based Artificial Intelligence-driven modelling for blank shape optimisation in sheet metal forming
File(s)
Published version
Author(s)
Zhou, Haosu
Li, Haoran
Zhao, Yingxue
Childs, Peter RN
Li, Nan
Type
Journal Article
Abstract
Design for manufacturing is essential to fully exploit the potential of emerging materials and processing technologies. However, traditional trial-and-error optimisation often exhibits inferior performance in manufacturability-driven problems, particularly when handling complex shapes. Surrogate modelling and optimisation have been widely investigated for efficiently predicting simulation results and enhancing manufacturability. Nevertheless, existing methods are mostly constrained by fixed shape parameterisation schemes, limiting their flexibility and effectiveness. To overcome this limitation, this research develops a non-parametric optimisation framework, validated on a sheet metal forming case study, specifically the blank shape optimisation of a hot-stamped B-pillar. The framework integrates an auto-decoder, serving as a differentiable blank shape generator, a convolutional neural network (CNN)-powered surrogate model for manufacturability evaluation, and an Adam optimiser for automated shape optimisation. The surrogate model predicts thickness distributions from the signed distance fields (SDFs) of blank shapes, which are generated by the auto-decoder from latent vectors; based on the predictions, the optimiser iteratively updates the latent vectors to acquire a blank shape with optimised manufacturability. The proposed framework demonstrates superior performance in terms of the accuracy of thickness distribution prediction, the fidelity of blank shape generation, and the efficiency of blank shape optimisation.
Date Issued
2025-08-01
Date Acceptance
2025-06-23
Citation
Materials and Design, 2025, 256
ISSN
0264-1275
Publisher
Elsevier
Journal / Book Title
Materials and Design
Volume
256
Copyright Statement
© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
10.1016/j.matdes.2025.114302
Subjects
Materials & Design Zhou
H.
Li
H.
Zhao
Y.
Childs
P.R.N.
Li
N.
Image-based Artificial Intelligencedriven modelling for blank shape optimisation in sheet metal forming
Materials & Design (2025)
doi: https://
Publication Status
Published
Article Number
114302
Date Publish Online
2025-06-24