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Estimation of the value of an inspection and maintenance program: A Bayesian gamma process model

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  • Yuan, Xian-Xun
  • Higo, Eishiro
  • Pandey, Mahesh D.

Abstract

This paper presents a model to quantify the economic value gained by implementation of an inspection and preventive maintenance program for managing an ageing component population. The proposed approach is a refinement of the Bayesian value of information analysis through the consideration of an intricate interaction between parameter and temporal uncertainties associated with the gamma process of degradation. This paper presents an analytical formulation and computational approach to solve this complex problem in a multivariate setting. The paper shows that the economic value is significantly sensitive to the prior information and relative costs of preventive and corrective maintenance. Since the value of inspection is dominated by a reduction in the parameter uncertainty of the gamma process model, lifecycle cost optimization which ignores this aspect would lead to a sub-optimal solution of the problem.

Suggested Citation

  • Yuan, Xian-Xun & Higo, Eishiro & Pandey, Mahesh D., 2021. "Estimation of the value of an inspection and maintenance program: A Bayesian gamma process model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004270
    DOI: 10.1016/j.ress.2021.107912
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    References listed on IDEAS

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    1. Fauriat, William & Zio, Enrico, 2020. "Optimization of an aperiodic sequential inspection and condition-based maintenance policy driven by value of information," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    2. Lozano, Jorge-Mario & Zuluaga, Santiago & Sánchez-Silva, Mauricio, 2020. "Developing flexible management strategies in infrastructure: The sequential expansion problem for infrastructure analysis (SEPIA)," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    3. Zou, Guang & Faber, Michael Havbro & González, Arturo & Banisoleiman, Kian, 2021. "Computing the value of information from periodic testing in holistic decision making under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    4. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part I: Theory," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 202-213.
    5. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    6. N. Bousquet & M. Fouladirad & A. Grall & C. Paroissin, 2015. "Bayesian gamma processes for optimizing condition‐based maintenance under uncertainty," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(3), pages 360-379, May.
    7. Malings, Carl & Pozzi, Matteo, 2016. "Value of information for spatially distributed systems: Application to sensor placement," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 219-233.
    8. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part II: POMDP implementation," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 214-224.
    9. Memarzadeh, Milad & Pozzi, Matteo, 2016. "Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 137-151.
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    Citations

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    Cited by:

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    5. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2022. "Optimal preventive switching of components in degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Esposito, Nicola & Mele, Agostino & Castanier, Bruno & GIORGIO, Massimiliano, 2023. "A hybrid maintenance policy for a deteriorating unit in the presence of three forms of variability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Zhu, Tiantian & Haugen, Stein & Liu, Yiliu & Yang, Xue, 2023. "A value of prediction model to estimate optimal response time to threats for accident prevention," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    8. Liu, Xingheng & Matias, José & Jäschke, Johannes & Vatn, Jørn, 2022. "Gibbs sampler for noisy Transformed Gamma process: Inference and remaining useful life estimation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    9. Mosayebi Omshi, E. & Shemehsavar, S. & Grall, A., 2024. "An intelligent maintenance policy for a latent degradation system," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Kim, Seokgoo & Choi, Joo-Ho & Kim, Nam Ho, 2022. "Inspection schedule for prognostics with uncertainty management," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    11. Zhang, Wei-Heng & Qin, Jianjun & Lu, Da-Gang & Liu, Min & Faber, Michael H., 2023. "Quantification of the value of condition monitoring system with time-varying monitoring performance in the context of risk-based inspection," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    12. Mendoza, Jorge & Bismut, Elizabeth & Straub, Daniel & Köhler, Jochen, 2022. "Optimal life-cycle mitigation of fatigue failure risk for structural systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).

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