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Chinese Journal of Management Science ›› 2024, Vol. 32 ›› Issue (8): 159-169.doi: 10.16381/j.cnki.issn1003-207x.2021.1584

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Integrated Design of Parameters and Tolerances under High-quality and Low-cost Perspective

Yunxia Han1,2,Yizhong Ma3(),Linhan Ouyang4,Jing Xu1,Guanxin Yao1   

  1. 1.Business School Jiangsu Mordern Logistics Base, Yangzhou University, Yangzhou 225127, China
    2.China Grand Canal Research Institute, Yangzhou 225127, China
    3.School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
    4.College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • Received:2021-08-10 Revised:2022-01-13 Online:2024-08-25 Published:2024-08-29
  • Contact: Yizhong Ma E-mail:yzma_2004@126.com

Abstract:

Due to the limitation of the experimental data or the unknown random effects in the experiment, it may lead to large errors in the parameters estimation during modeling process, and a reliable quality design cannot be obtained.Therefore, the joint confidence region is constructed to quantify the uncertainty of input parameters (model parameters and parameters to be estimated in noise variables).Secondly, according to the distribution information of noise variable and design variable tolerance, a new expected quality loss function based on the confidence region is proposed.Then from the perspective of robustness and economy, optimization object function is constructed based on the interval estimation theory, which includes the location and dispersion effects of quality loss and tolerance cost.Finally, the effectiveness of the proposed method is verified by experimental simulation and industrial example.The results show that the method simultaneously incorporates the two important uncertainty into the objective function. It not only has good robustness to the disturbance of uncertainty, but also can make a reasonable trade-off between quality loss and tolerance cost to achieve a lower total cost.

Key words: input parameter uncertainty, integrated design of parameters and tolerances, interval estimation, economic quality design

CLC Number: