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On the effect of downtime costs and budget constraint on preventive and replacement policies

Author

Listed:
  • Pascual, R.
  • Meruane, V.
  • Rey, P.A.

Abstract

This work proposes a general approach to study and improve the effectiveness of the system with respect to its expected life-cycle cost rate. The model we propose considers a production system which is protected against demand fluctuations and failure occurrences with elements like stock piles, line and equipment redundancy, and the use of alternative production methods. These design policies allow to keep or minimize the effect on the nominal throughput, while corrective measures are taken. The system is also subject to an aging process which depends on the frequency and quality of preventive actions. Making decisions is difficult because of discontinuities in intervention and downtime costs and the limited budget. We present a non-linear mixed integer formulation that minimizes the expected overall cost rate with respect to repair, overhaul and replacement times and the overhaul improvement factor proposed in the literature. The model is deterministic and considers minimal repairs and imperfect overhauls. We illustrate its application with a case based on a known benchmark example.

Suggested Citation

  • Pascual, R. & Meruane, V. & Rey, P.A., 2008. "On the effect of downtime costs and budget constraint on preventive and replacement policies," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 144-151.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:1:p:144-151
    DOI: 10.1016/j.ress.2006.12.002
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    References listed on IDEAS

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    1. Pascual, R. & Ortega, J.H., 2006. "Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 241-248.
    2. Scarf, Philip A., 1997. "On the application of mathematical models in maintenance," European Journal of Operational Research, Elsevier, vol. 99(3), pages 493-506, June.
    3. Komonen, Kari, 2002. "A cost model of industrial maintenance for profitability analysis and benchmarking," International Journal of Production Economics, Elsevier, vol. 79(1), pages 15-31, September.
    4. David Edwards & Gary Holt & Frank Harris, 2000. "A model for predicting plant maintenance costs," Construction Management and Economics, Taylor & Francis Journals, vol. 18(1), pages 65-75.
    5. Pham, Hoang & Wang, Hongzhou, 1996. "Imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 94(3), pages 425-438, November.
    6. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    7. Rommert Dekker & Ralph Wildeman & Frank Duyn Schouten, 1997. "A review of multi-component maintenance models with economic dependence," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 45(3), pages 411-435, October.
    8. David Edwards & Gary Holt & Frank Harris, 2002. "Predicting downtime costs of tracked hydraulic excavators operating in the UK opencast mining industry," Construction Management and Economics, Taylor & Francis Journals, vol. 20(7), pages 581-591.
    9. Wildeman, R. E. & Dekker, R. & Smit, A. C. J. M., 1997. "A dynamic policy for grouping maintenance activities," European Journal of Operational Research, Elsevier, vol. 99(3), pages 530-551, June.
    10. K A H Kobbacy & J Jeon, 2001. "The development of a hybrid intelligent maintenance optimisation system (HIMOS)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(7), pages 762-778, July.
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    Citations

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    Cited by:

    1. Markus Bohlin & Mathias Wärja, 2015. "Maintenance optimization with duration-dependent costs," Annals of Operations Research, Springer, vol. 224(1), pages 1-23, January.
    2. Diaz, Nicole & Pascual, Rodrigo & Ruggeri, Fabrizio & López Droguett, Enrique, 2017. "Modelling age replacement policy under multiple time scales and stochastic usage profiles," International Journal of Production Economics, Elsevier, vol. 188(C), pages 22-28.
    3. Gary, Linnéusson & Amos, Ng H.C. & Tehseen, Aslam, 2018. "Towards strategic development of maintenance and its effects on production performance by using system dynamics in the automotive industry," International Journal of Production Economics, Elsevier, vol. 200(C), pages 151-169.
    4. Pascual, R. & Del Castillo, G. & Louit, D. & Knights, P., 2009. "Business-oriented prioritization: A novel graphical technique," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1308-1313.
    5. Andrea Trianni & Davide Accordini & Enrico Cagno, 2020. "Identification and Categorization of Factors Affecting the Adoption of Energy Efficiency Measures within Compressed Air Systems," Energies, MDPI, vol. 13(19), pages 1-51, October.

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