There are process uncertainties and material property variations during laminated steel sheet forming, and those fluctuations may result in non-reliable forming quality issues such as fracture and delamination. Additionally, the optimization of sheet forming process is a typical multi-objective optimization problem. The target is to find a multi-objective design optimization and improve the process design reliability for laminated sheet metal forming. The paper aims to discuss these issues.
Desirability function approach is adopted to conduct deterministic multi-objective optimization, and response surface is used as meta-model. Reliability analysis is conducted to evaluate the robustness of the multi-objective design optimization. The proposed method is implemented in a step-bottom square cup drawing process. First, forming process parameters and three noise factors are assumed as probability variables to conduct reliability assessment of the laminated steel sheet forming process using Monte Carlo simulation. Next, only two forming process parameters, blank holding force and frictional coefficient, are considered as probability variables to investigate the influence of the forming parameter deviation on the variance of the response using the first-order second-moment method.
The results indicate that multi-objective design optimization using desirability function method has high efficiency, and an optimized robust design can be obtained after reliability assessment.
The proposed design procedure has potential as a simple and practical approach in the laminated steel sheet forming process.
This research was funded by the National Natural Science Foundation of China through Grant No. 50775142. The authors also thank Baoshan Steel & Iron Co. China, who provided the laminated steel sheets.
Li, H., Chen, J. and Xiao, Y. (2013), "Multi-objective optimization for laminated steel sheet forming process based on desirability function approach and reliability analysis", Engineering Computations, Vol. 30 No. 8, pp. 1107-1127. https://doi.org/10.1108/EC-08-2012-0179Download as .RIS
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