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Periodic replacement strategies: optimality conditions and numerical performance comparisons

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  • Mohamed Larbi Rebaiaia
  • Daoud Ait-kadi
  • Afshin Jamshidi

Abstract

In maintenance engineering, age replacement policy (ARP) and block replacement policy (BRP) are the most popular basic strategies. They have been intensively studied and compared using different performance measures. Several of these comparisons are stochastics on the basis of the renewal theory, and a few of them are of economic benefit. This paper presents a comparative study for analysing ARP and BRP models using the expected costs function as the principal criterion. To provide this comparison, we propose a numerical approach allowing to combine cost/distribution for the determination of the optimal strategy. For that, we resume the main analytical results and prove that a finite solution exists if the failure rate increases. Results clearly show that both strategies are very close, which intuitively confirm the statement of Barlow and Proschan’s theorem. Based on the computational results, we show that the ultimate decision to select the best strategy is conditioned by the choice of the distribution function, the value of its parameters and that the periodic replacement unit cost must be much lower than the replacement unit cost at failure.

Suggested Citation

  • Mohamed Larbi Rebaiaia & Daoud Ait-kadi & Afshin Jamshidi, 2017. "Periodic replacement strategies: optimality conditions and numerical performance comparisons," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7135-7152, December.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:23:p:7135-7152
    DOI: 10.1080/00207543.2017.1349953
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    References listed on IDEAS

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    1. Berg, Menachem, 1980. "A marginal cost analysis for prevetive replacement policies," European Journal of Operational Research, Elsevier, vol. 4(2), pages 136-142, February.
    2. Khaled El-Akruti & Tieling Zhang & Richard Dwight, 2016. "Developing an optimum maintenance policy by life cycle cost analysis – a case study," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5946-5962, October.
    3. Chaudhry, Mohan & Fisher, Brent, 2013. "Simple and elegant derivations for some asymptotic results in the discrete-time renewal process," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 315-319.
    4. George H. Weiss, 1956. "On the theory of replacement of machinery with a random failure time," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(4), pages 279-293, December.
    5. Richard Barlow & Larry Hunter, 1960. "Optimum Preventive Maintenance Policies," Operations Research, INFORMS, vol. 8(1), pages 90-100, February.
    6. R. Cléroux & S. Dubuc & C. Tilquin, 1979. "The Age Replacement Problem with Minimal Repair and Random Repair Costs," Operations Research, INFORMS, vol. 27(6), pages 1158-1167, December.
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    Cited by:

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    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.

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