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Predictive maintenance for the heated hold-up tank

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  • de Saporta, Benoîte
  • Zhang, Huilong

Abstract

We present a numerical method to compute an optimal maintenance date for the test case of the heated hold-up tank. The system consists of a tank containing a fluid whose level is controlled by three components: two inlet pumps and one outlet valve. A thermal power source heats up the fluid. The failure rates of the components depends on the temperature, the position of the three components monitors the liquid level in the tank and the liquid level determines the temperature. Therefore, this system can be modeled by a hybrid process where the discrete (components) and continuous (level, temperature) parts interact in a closed loop. We model the system by a piecewise deterministic Markov process, propose and implement a numerical method to compute the optimal maintenance date to repair the components before the total failure of the system.

Suggested Citation

  • de Saporta, Benoîte & Zhang, Huilong, 2013. "Predictive maintenance for the heated hold-up tank," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 82-90.
    • Handle: RePEc:eee:reensy:v:115:y:2013:i:c:p:82-90
    DOI: 10.1016/j.ress.2013.02.016
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    References listed on IDEAS

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    1. H Zhang & F Dufour & Y Dutuit & K Gonzalez, 2008. "Piecewise deterministic Markov processes and dynamic reliability," Journal of Risk and Reliability, , vol. 222(4), pages 545-551, December.
    2. B de Saporta & F Dufour & H Zhang & C Elegbede, 2012. "Optimal stopping for the predictive maintenance of a structure subject to corrosion," Journal of Risk and Reliability, , vol. 226(2), pages 169-181, April.
    3. 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.
    4. Li, Jinghui & Mosleh, Ali & Kang, Rui, 2011. "Likelihood ratio gradient estimation for dynamic reliability applications," Reliability Engineering and System Safety, Elsevier, vol. 96(12), pages 1667-1679.
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    Cited by:

    1. Yang, Jun & Aldemir, Tunc, 2016. "An algorithm for the computationally efficient deductive implementation of the Markov/Cell-to-Cell-Mapping Technique for risk significant scenario identification," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 1-8.

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