Abstract
A multi-objective reliability-based design optimization was proposed to optimize the cooling system parameters with regard to cooling efficiency and structure reliability. To address the contradictions between cooling capacity and mechanical strength of hot-stamping die, energy balance principle and simplified mechanical models were investigated. The multi-objective particle swarm optimization (MOPSO) algorithm coupled with Monte Carlo simulation (MCS) was employed to obtain the optimal reliable design solutions. Based on the proposed method, an optimal automobile component was given and manufactured with material 22MnB5, and the strength of formed part was evaluated by the tensile test, micro-structure distribution, and micro-Vickers hardness. The numerical results showed that there was a trade-off between the desired reliability level and objective performance because deterministic optimization generated the best cooling capacity while its reliability was the lowest. It is noted that the cooling capacity has a negative effect on reliability. The cooling structural parameters satisfied the requirement because the tensile strength, micro-Vickers hardness, and uniform distribution of martensite of samples are validated.
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