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Bayesian reliability analysis of complex repairable systems

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  • Antonio Pievatolo
  • Fabrizio Ruggeri

Abstract

Stemming from a consulting project about a gas distribution network, a new, Bayesian model is proposed to describe failures in a complex, expanding over time, repairable system, which is split into components installed over different years. Both exchangeable and independent Poisson processes, homogeneous in space but not in time, are used to model the components. The model takes also into account missing data, due either to unrecorded early failures or unknown installation dates of failed parts. Actual escape data from a gas distribution network illustrate the implementation of the model, which relies on the use of Markov chain Monte Carlo methods. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Antonio Pievatolo & Fabrizio Ruggeri, 2004. "Bayesian reliability analysis of complex repairable systems," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 20(3), pages 253-264, July.
    • Handle: RePEc:wly:apsmbi:v:20:y:2004:i:3:p:253-264
    DOI: 10.1002/asmb.522
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    Cited by:

    1. Antonio Pievatolo & Fabrizio Ruggeri & Refik Soyer & Simon Wilson, 2021. "Decisions in Risk and Reliability: An Explanatory Perspective," Stats, MDPI, vol. 4(2), pages 1-23, March.
    2. Hermann, Simone & Ickstadt, Katja & Müller, Christine H., 2018. "Bayesian prediction for a jump diffusion process – With application to crack growth in fatigue experiments," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 83-96.
    3. Insua, David Rios & Ruggeri, Fabrizio & Soyer, Refik & Wilson, Simon, 2020. "Advances in Bayesian decision making in reliability," European Journal of Operational Research, Elsevier, vol. 282(1), pages 1-18.
    4. Kaan Kuzu & Refik Soyer, 2018. "Bayesian modeling of abandonments in ticket queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 499-521, September.
    5. Fabrizio Ruggeri, 2014. "On Some Optimal Bayesian Nonparametric Rules for Estimating Distribution Functions," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 289-304, June.
    6. Ravishanker, Nalini & Liu, Zhaohui & Ray, Bonnie K., 2008. "NHPP models with Markov switching for software reliability," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 3988-3999, April.

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