This study demonstrates improved dimensional accuracy in aluminum alloy stamping dies, suggesting effective compensation and optimization methods.
This study aims at the deformation compensation and multi-parameter process optimization of aluminum alloy profile stamping to solve the influence of die deformation on product quality. By optimizing the die design to compensate for die deformation and minimize the shape error, a multi-parameter process optimization scheme is proposed to improve stamping efficiency, reduce material waste, and improve dimensional accuracy. A theoretical model of die deformation during stamping is established, and finite element analysis (FEA) is used to simulate the influence of various process parameters. Optimization algorithms such as genetic algorithm and particle swarm algorithm are used to perform multi-objective optimization and adjustment on key parameters such as stamping speed, temperature, and material properties. The experiment verifies the effectiveness of the proposed compensation optimization method, and the product quality and production efficiency are significantly improved. This study provides a practical solution for the optimization of aluminum alloy stamping process in industrial applications.
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Yang et al. (2025) studied this question.
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