Iterations in optimization and numerical simulation for the sheet metal forming process may lead to extensive computation. In addition, uncertainties in materials or processing parameters may have great influence on t...Iterations in optimization and numerical simulation for the sheet metal forming process may lead to extensive computation. In addition, uncertainties in materials or processing parameters may have great influence on the design quality. A six sigma optimization method is proposed, by combining the dual response surface method (DRSM) and six sigma philosophy, to save computation cost and improve reliability and robustness of parts. Using this method, statistical technology, including the design of experiment and analysis of variance, approximate model and six sigma philosophy are integrated together to achieve improved quality. Two sheet metal forming processes are provided as examples to illustrate the proposed method.展开更多
Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the tran...Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the transitional region may be deteriorated by uncontrollable factors, such as the manufacturing tolerance of the preforming billet, fluctuation of the stroke length, and friction factor. Thus, a dual-response surface method (RSM)-based robust optimization of the billet was proposed to address the uncontrollable factors in transi- tional region of the ILLF. Given that the die underfilling and folding defect are two key factors that influence the forming quality of the transitional region, minimizing the mean and standard deviation of the die underfilling rate and avoiding folding defect were defined as the objective function and constraint condition in robust optimization. Then, the cross array design was constructed, a dual-RSM model was established for the mean and standard deviation of the die underfilling rate by considering the size parameters of the billet and uncontrollable factors. Subsequently, an optimum solution was derived to achieve the robust optimization of the billet. A case study on robust optimization was conducted. Good results were attained for improving the die filling and avoiding folding defect, suggesting that the robust optimization of the billet in the transitional region of the ILLF was efficient and reliable.展开更多
基金This project is supported by National Natural Science Foundation of China (No.50475020).
文摘Iterations in optimization and numerical simulation for the sheet metal forming process may lead to extensive computation. In addition, uncertainties in materials or processing parameters may have great influence on the design quality. A six sigma optimization method is proposed, by combining the dual response surface method (DRSM) and six sigma philosophy, to save computation cost and improve reliability and robustness of parts. Using this method, statistical technology, including the design of experiment and analysis of variance, approximate model and six sigma philosophy are integrated together to achieve improved quality. Two sheet metal forming processes are provided as examples to illustrate the proposed method.
基金Acknowledgements The authors would like to gratefully acknowledge the support given by the National Natural Science Foundation of China (Grant No. 51575449), Research Fund of the State Key Laboratory of Solidification Processing (NWPU), China (Grant No. 104-QP-2014), 111 Project (Grant No. B08040), and Fundamental Research Funds for the Central Universities (Grant No. 3102015AX004).
文摘Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the transitional region may be deteriorated by uncontrollable factors, such as the manufacturing tolerance of the preforming billet, fluctuation of the stroke length, and friction factor. Thus, a dual-response surface method (RSM)-based robust optimization of the billet was proposed to address the uncontrollable factors in transi- tional region of the ILLF. Given that the die underfilling and folding defect are two key factors that influence the forming quality of the transitional region, minimizing the mean and standard deviation of the die underfilling rate and avoiding folding defect were defined as the objective function and constraint condition in robust optimization. Then, the cross array design was constructed, a dual-RSM model was established for the mean and standard deviation of the die underfilling rate by considering the size parameters of the billet and uncontrollable factors. Subsequently, an optimum solution was derived to achieve the robust optimization of the billet. A case study on robust optimization was conducted. Good results were attained for improving the die filling and avoiding folding defect, suggesting that the robust optimization of the billet in the transitional region of the ILLF was efficient and reliable.