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Criticality measures for components with multi-dimensional degradation

Author

Listed:
  • Xiao Liu
  • Khalifa N. Al-Khalifa
  • Elsayed A. Elsayed
  • David W. Coit
  • Abdelmagid S. Hamouda

Abstract

Failures of engineering structures and equipment are often attributed to the failure of a single component. Hence, it is important to identify critical components in a system and understand how a component's criticality changes over time under dynamic environments. This article investigates the criticality analysis for components with multiple competing failure modes due to degradation. The component degradation is modeled as a k-dimensional Wiener process. A component fails when any of the k degradation processes associated with that component attains a certain threshold level. Motivated by Nelson's cumulative exposure model, a relationship between both the mean and diffusion of the degradation process and environmental conditions is established. Expressions of a component's criticality measures are derived. Numerical examples are presented to illustrate the criticality analysis.

Suggested Citation

  • Xiao Liu & Khalifa N. Al-Khalifa & Elsayed A. Elsayed & David W. Coit & Abdelmagid S. Hamouda, 2014. "Criticality measures for components with multi-dimensional degradation," IISE Transactions, Taylor & Francis Journals, vol. 46(10), pages 987-998, October.
    • Handle: RePEc:taf:uiiexx:v:46:y:2014:i:10:p:987-998
    DOI: 10.1080/0740817X.2013.851433
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    Cited by:

    1. Lanqing Hong & Zhi-Sheng Ye & Ran Ling, 2018. "Environmental Risk Assessment of Emerging Contaminants Using Degradation Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 390-409, September.
    2. Fang, Guanqi & Pan, Rong & Wang, Yukun, 2022. "Inverse Gaussian processes with correlated random effects for multivariate degradation modeling," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1177-1193.
    3. Yan, Bingxin & Ma, Xiaobing & Yang, Li & Wang, Han & Wu, Tianyi, 2020. "A novel degradation-rate-volatility related effect Wiener process model with its extension to accelerated ageing data analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    4. Huynh, K.T. & Vu, H.C. & Nguyen, T.D. & Ho, A.C., 2022. "A predictive maintenance model for k-out-of-n:F continuously deteriorating systems subject to stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Liu, Bin & Zhao, Xiujie & Liu, Guoquan & Liu, Yiqi, 2020. "Life cycle cost analysis considering multiple dependent degradation processes and environmental influence," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    6. 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.

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