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Degradation models and implied lifetime distributions

Author

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  • Bae, Suk Joo
  • Kuo, Way
  • Kvam, Paul H.

Abstract

In experiments where failure times are sparse, degradation analysis is useful for the analysis of failure time distributions in reliability studies. This research investigates the link between a practitioner's selected degradation model and the resulting lifetime model. Simple additive and multiplicative models with single random effects are featured. Results show that seemingly innocuous assumptions of the degradation path create surprising restrictions on the lifetime distribution. These constraints are described in terms of failure rate and distribution classes.

Suggested Citation

  • Bae, Suk Joo & Kuo, Way & Kvam, Paul H., 2007. "Degradation models and implied lifetime distributions," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 601-608.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:5:p:601-608
    DOI: 10.1016/j.ress.2006.02.002
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    Cited by:

    1. Zhang, Jianchun & Li, Lei & Chen, Zhiwei, 2021. "Strength–redundancy allocation problem using artificial bee colony algorithm for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Zhang, Jianchun & Zhao, Yu & Ma, Xiaobing, 2019. "A new reliability analysis method for load-sharing k-out-of-n: F system based on load-strength model," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 152-165.
    3. Keedy, Elias & Feng, Qianmei, 2012. "A physics-of-failure based reliability and maintenance modeling framework for stent deployment and operation," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 94-101.
    4. 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.
    5. Filippo De Carlo & Orlando Borgia & Mario Tucci, 2014. "Accelerated degradation tests for reliability estimation of a new product: A case study for washing machines," Journal of Risk and Reliability, , vol. 228(2), pages 127-138, April.
    6. Zhang, Jianchun & Zhao, Yu & Ma, Xiaobing, 2020. "Reliability modeling methods for load-sharing k-out-of-n system subject to discrete external load," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    7. Wang, Huan & Wang, Guan-jun & Duan, Feng-jun, 2016. "Planning of step-stress accelerated degradation test based on the inverse Gaussian process," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 97-105.
    8. Dejing Kong & Lirong Cui, 2016. "Bayesian inference of multi-stage reliability for degradation systems with calibrations," Journal of Risk and Reliability, , vol. 230(1), pages 18-33, February.
    9. Peng, Weiwen & Li, Yan-Feng & Yang, Yuan-Jian & Huang, Hong-Zhong & Zuo, Ming J., 2014. "Inverse Gaussian process models for degradation analysis: A Bayesian perspective," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 175-189.
    10. Ching, Jianye & Leu, Sou-Sen, 2009. "Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1962-1974.
    11. Li, Zan & Wang, Fengming & Wang, Chengjie & Hu, Qingpei & Yu, Dan, 2021. "Reliability modeling and evaluation of lifetime delayed degradation process with nondestructive testing," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    12. Peng, Weiwen & Li, Yan-Feng & Mi, Jinhua & Yu, Le & Huang, Hong-Zhong, 2016. "Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 75-87.
    13. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    14. Wang, Jia & Bai, Guanghan & Li, Zhigang & Zuo, Ming J., 2020. "A general discrete degradation model with fatal shocks and age- and state-dependent nonfatal shocks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    15. Peihua Jiang, 2022. "Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    16. Dong, Wenjie & Liu, Sifeng & Bae, Suk Joo & Cao, Yingsai, 2021. "Reliability modelling for multi-component systems subject to stochastic deterioration and generalized cumulative shock damages," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    17. Liu, Di & Wang, Shaoping & Zhang, Chao & Tomovic, Mileta, 2018. "Bayesian model averaging based reliability analysis method for monotonic degradation dataset based on inverse Gaussian process and Gamma process," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 25-38.

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