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A new class of survival distribution for degradation processes subject to shocks

Author

Listed:
  • Mei-Ling Ting Lee

    (School of Public Health, University of Maryland
    Biostatistics and Risk Assessment Center, University of Maryland)

  • G. A. Whitmore

    (McGill University
    Ottawa Hospital Research Institute)

Abstract

Many systems experience gradual degradation while simultaneously being exposed to a stream of random shocks of varying magnitudes that eventually cause failure when a shock exceeds the residual strength of the system. In this paper, we present a family of stochastic processes, called shock-degradation processes, that describe this failure mechanism. In our failure model, system strength follows a geometric degradation process. The degradation process itself is any Lévy process, that is, any stochastic process with stationary independent increments. The shock stream is a Fréchet stochastic process, a process derived from the Fréchet extreme-value distribution. Finally, the shock-degradation process is a convolution of the Fréchet shock process and any one of the candidate degradation processes. The system fails at the first occasion when a shock takes system strength across a threshold at zero. The paper presents results for Wiener diffusion processes and gamma processes as examples of Lévy degradation processes. The paper develops key statistical properties of the process model and its survival distribution, including several that are important for its practical application. As the failure mechanism is a first hitting time event, applications that require regression structures fall within the domain of threshold regression methodology.

Suggested Citation

  • Mei-Ling Ting Lee & G. A. Whitmore, 2019. "A new class of survival distribution for degradation processes subject to shocks," Journal of Statistical Distributions and Applications, Springer, vol. 6(1), pages 1-24, December.
  • Handle: RePEc:spr:jstada:v:6:y:2019:i:1:d:10.1186_s40488-019-0095-1
    DOI: 10.1186/s40488-019-0095-1
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    References listed on IDEAS

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    1. Gauss M. Cordeiro & Giovana O. Silva & Edwin M. M. Ortega, 2016. "An extended-G geometric family," Journal of Statistical Distributions and Applications, Springer, vol. 3(1), pages 1-16, December.
    2. 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.
    3. Mercier, Sophie & Pham, Hai Ha, 2017. "A bivariate failure time model with random shocks and mixed effects," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 33-51.
    4. Zhi‐Sheng Ye & Min Xie, 2015. "Stochastic modelling and analysis of degradation for highly reliable products," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(1), pages 16-32, January.
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