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Reliability modeling-based tolerance design and process parameter analysis considering performance degradation

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  • Kong, Xuefeng
  • Yang, Jun
  • Hao, Songhua

Abstract

Tolerance design and process parameter analysis have been widely used for reducing the fluctuation of product quality characteristics (QCs). Most existing works focus on finding the best compromise between manufacturing cost and tolerance of QCs. However, the performance degradation of products will lead to QCs deviating from design specifications, which is ignored in current researches. Motivated by the stress relaxation process of helical springs, we propose a more reliable tolerance design and process parameter analysis considering performance degradation. An accelerated degradation model is first constructed to reflect the degradation process of helical springs and the influence of the initial free length. Subsequently, considering the given reliability constraint, a tolerance design method based on degradation performance is developed to guide the quality improvement of helical springs. Furthermore, a new reliability model embodied with the influence of parameter fluctuation is proposed, and an allowable fluctuation range for the deviation and variance of the initial free length is derived, based on which the process parameter can be optimized to improve the manufacturing process. Finally, a real case study of helical springs is conducted to illustrate the implementation and effectiveness of the proposed method.

Suggested Citation

  • Kong, Xuefeng & Yang, Jun & Hao, Songhua, 2021. "Reliability modeling-based tolerance design and process parameter analysis considering performance degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    • Handle: RePEc:eee:reensy:v:207:y:2021:i:c:s0951832020308358
    DOI: 10.1016/j.ress.2020.107343
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    References listed on IDEAS

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    5. Yousefi, Nooshin & Coit, David W. & Song, Sanling, 2020. "Reliability analysis of systems considering clusters of dependent degrading components," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    6. Zhi‐Sheng Ye & Min Xie, 2015. "Rejoinder to ‘Stochastic modelling and analysis of degradation for highly reliable products’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(1), pages 35-36, January.
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    Cited by:

    1. Zheng, Bokai & Chen, Cen & Lin, Yigang & Hu, Yifan & Ye, Xuerong & Zhai, Guofu & Zio, Enrico, 2022. "Optimal design of step-stress accelerated degradation test oriented by nonlinear and distributed degradation process," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    2. Huang, Peng & Gu, Yingkui & Li, He & Yazdi, Mohammad & Qiu, Guangqi, 2023. "An Optimal Tolerance Design Approach of Robot Manipulators for Positioning Accuracy Reliability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Wang, Guodong & Shao, Mengying & Lv, Shanshan & Kong, Xiangfen & He, Zhen & Vining, Geoff, 2022. "Process parameter optimization for lifetime improvement experiments considering warranty and customer satisfaction," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

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