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A nonlinear Wiener degradation model integrating degradation data under accelerated stresses and real operating environment

Author

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  • Li Sun
  • Fangchao Zhao
  • Narayanaswamy Balakrishnan
  • Honggen Zhou
  • Xiaohui Gu

Abstract

Remaining useful life (RUL) prediction in real operating environment (ROE) plays an important role in condition-based maintenance. However, the life information in ROE is limited, especially for some long-life products. In such cases, accelerated degradation test (ADT) is an effective method to collect data and then the accelerated degradation data are converted to normal level of accelerated stresses through acceleration factors. However, the stresses in ROE are different from normal stresses since there are some other stresses except normal stresses, which cannot be accelerated, but still have impact on the degradation. To predict the RUL in ROE, a nonlinear Wiener degradation model is proposed based on failure mechanism invariant principle which is the precondition and requirement of an ADT and a calibration factor is introduced to calibrate the difference between ROE and normal stresses. Moreover, the unit-to-unit variability is considered in the concern model. Based upon the proposed approach, the RUL distribution is derived in closed form. The unknown parameters in the model are obtained by a new two-step method through fuzing converted degradation data in normal stresses and degradation data in ROE. Finally, the validity of the proposed model is demonstrated through several simulation data and a case study.

Suggested Citation

  • Li Sun & Fangchao Zhao & Narayanaswamy Balakrishnan & Honggen Zhou & Xiaohui Gu, 2021. "A nonlinear Wiener degradation model integrating degradation data under accelerated stresses and real operating environment," Journal of Risk and Reliability, , vol. 235(3), pages 356-373, June.
    • Handle: RePEc:sae:risrel:v:235:y:2021:i:3:p:356-373
    DOI: 10.1177/1748006X20978099
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    References listed on IDEAS

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    1. Wang, Lizhi & Pan, Rong & Li, Xiaoyang & Jiang, Tongmin, 2013. "A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 38-47.
    2. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    3. Massimiliano Giorgio & Fabio Postiglione & Gianpaolo Pulcini, 2020. "Bayesian estimation and prediction for the transformed Wiener degradation process," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(4), pages 660-678, July.
    4. Wang, Xiao, 2010. "Wiener processes with random effects for degradation data," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 340-351, February.
    5. Nguyen, Khanh T.P. & Fouladirad, Mitra & Grall, Antoine, 2018. "Model selection for degradation modeling and prognosis with health monitoring data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 105-116.
    6. Si, Xiao-Sheng & Chen, Mao-Yin & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2013. "Specifying measurement errors for required lifetime estimation performance," European Journal of Operational Research, Elsevier, vol. 231(3), pages 631-644.
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    Cited by:

    1. Saberzadeh, Zahra & Razmkhah, Mostafa & Amini, Mohammad, 2023. "Bayesian reliability analysis of complex k-out-of-n: â„“ systems under degradation performance," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    2. Saberzadeh, Zahra & Razmkhah, Mostafa, 2022. "Reliability of degrading complex systems with two dependent components per element," Reliability Engineering and System Safety, Elsevier, vol. 222(C).

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