Optimization of stamping and forming process parameters for sink based on BP-PSO algorithm

Cuixin Chen; Duan Mei

doi:10.1117/12.2631618

18 March 2022 Optimization of stamping and forming process parameters for sink based on BP-PSO algorithm

Cuixin Chen, Duan Mei

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121682Z (2022) https://doi.org/10.1117/12.2631618
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

By optimizing the process parameters, we can reduce the die trial time, lower the production cost and improve the forming quality of the stamped parts. Taking cistern forming as an example, a computer aided engineering model was established to reduce the maximum thinning rate. The back propagation (BP) neural network was trained by combining the partial factor test method with the numerical simulation of stamping process, using the friction coefficient, die clearance, sheet thickness, binder force and the drag coefficient of the draw bead obtained from the simulation experiments as input values and the maximum thinning rate as output values. Particle swarm optimization (PSO) was used to optimize the stamping process parameters. The conclusion has guiding significance for stamping process design.

Citation Download Citation

Cuixin Chen and Duan Mei "Optimization of stamping and forming process parameters for sink based on BP-PSO algorithm", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121682Z (18 March 2022); https://doi.org/10.1117/12.2631618

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