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A modified quality loss model of service life prediction for products via wear regularity

Author

Listed:
  • Liu, Xintian
  • Mao, Kui
  • Wang, Xiaolan
  • Wang, Xu
  • Wang, Yansong

Abstract

It is very important to consider the life change regularity of products during full life-cycle based on product geometric quality characteristics. The relationship between product quality loss and service life distribution is analyzed to estimate the average life of products during service time, and the range of concentrated distribution of product service life is determined. To estimate the quality loss of products more accurately, the viewpoint is put forward that the main quality characteristic values should obey the nonlinear change during service time. Then, the service quality loss function (QLF) is modified based on the wear regularity. The effect of different parameters on the average service life of products is discussed with practical case, such as design, production and service parameters. A new research method is proposed on the full life-cycle variation rule of mechanical products.

Suggested Citation

  • Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
  • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020306888
    DOI: 10.1016/j.ress.2020.107187
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    References listed on IDEAS

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    1. Shuangshuang Li & Xintian Liu & Yansong Wang & Xiaolan Wang, 2018. "Hidden quality cost function of a product based on the cubic approximation of the Taylor expansion," International Journal of Production Research, Taylor & Francis Journals, vol. 56(14), pages 4762-4780, July.
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    Cited by:

    1. Yue-Yi Zhang & Han-Ting Zhou & Ijaz Younis & Li Zhou, 2021. "Coupling Coordination Analysis of Technological Innovation, Standards, and Quality: Evidence From China," SAGE Open, , vol. 11(3), pages 21582440211, July.
    2. 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).
    3. Zhou, Zhihao & Zhang, Wei & Yao, Peng & Long, Zhenhua & Bai, Mingling & Liu, Jinfu & Yu, Daren, 2024. "More realistic degradation trend prediction for gas turbine based on factor analysis and multiple penalty mechanism loss function," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    4. Ghaderi, A. & Hassani, H. & Khodaygan, S., 2021. "A Bayesian-reliability based multi-objective optimization for tolerance design of mechanical assemblies," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    5. Liu, Xintian & Yu, Xueguang & Tong, Jiachi & Wang, Xu & Wang, Xiaolan, 2021. "Mixed uncertainty analysis for dynamic reliability of mechanical structures considering residual strength," Reliability Engineering and System Safety, Elsevier, vol. 209(C).

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