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Parametric inference for multiple repairable systems under dependent competing risks

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  • Anupap Somboonsavatdee
  • Ananda Sen

Abstract

The focus of this article is on the analysis of repairable systems that are subject to multiple sources of recurrence. The event of interest at the system level is assumed to be caused by the earliest occurrence of a source, thereby conforming to a series system competing risks framework. Parametric inference is carried out under the power law process model that has found significant attention in industrial applications. Dependence among the cause‐specific recurrent processes is induced via a shared frailty structure. The theoretical inference results are implemented to a warranty database for a fleet of automobiles, for which the warranty repair is triggered by the failure of one of many components. Extensive finite‐sample simulation is carried out to supplement the asymptotic findings. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Anupap Somboonsavatdee & Ananda Sen, 2015. "Parametric inference for multiple repairable systems under dependent competing risks," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 706-720, September.
    • Handle: RePEc:wly:apsmbi:v:31:y:2015:i:5:p:706-720
    DOI: 10.1002/asmb.2079
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    Cited by:

    1. Almeida, Marco Pollo & Paixão, Rafael S. & Ramos, Pedro L. & Tomazella, Vera & Louzada, Francisco & Ehlers, Ricardo S., 2020. "Bayesian non-parametric frailty model for dependent competing risks in a repairable systems framework," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    2. Luo, Ming & Wu, Shaomin, 2019. "A comprehensive analysis of warranty claims and optimal policies," European Journal of Operational Research, Elsevier, vol. 276(1), pages 144-159.
    3. M. S. Sisuma & P. G. Sankaran, 2022. "Non-parametric test of recurrent cumulative incidence functions for competing risks models," METRON, Springer;Sapienza Università di Roma, vol. 80(3), pages 331-342, December.

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