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Minimum Cost Replacement Under Markovian Deterioration

Author

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  • Peter Kolesar

    (Columbia University)

Abstract

Conditions are derived under which optimal replacement rules for systems subject to Markovian deterioration and failure are given by control limit replacement rules. An efficient method of deriving such rules is given which is based on the simplex algorithm.

Suggested Citation

  • Peter Kolesar, 1966. "Minimum Cost Replacement Under Markovian Deterioration," Management Science, INFORMS, vol. 12(9), pages 694-706, May.
    • Handle: RePEc:inm:ormnsc:v:12:y:1966:i:9:p:694-706
    DOI: 10.1287/mnsc.12.9.694
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    Cited by:

    1. Panagiotidou, S. & Tagaras, G., 2012. "Optimal integrated process control and maintenance under general deterioration," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 58-70.
    2. Linguo Gong & James Pruett & Kwei Tang, 1997. "A Markovian model for process setup and improvement," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(4), pages 383-400, June.
    3. Kut C. So, 1992. "Optimality of control limit policies in replacement models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(5), pages 685-697, August.
    4. Ece Zeliha Demirci & Joachim Arts & Geert-Jan Van Houtum, 2022. "A restless bandit approach for capacitated condition based maintenance scheduling," DEM Discussion Paper Series 22-01, Department of Economics at the University of Luxembourg.
    5. Alan P. Wood, 1988. "Optimal maintenance policies for constantly monitored systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(4), pages 461-471, August.
    6. Hsieh, Chung-Chi & Chiu, Kuo-Chang, 2002. "Optimal maintenance policy in a multistate deteriorating standby system," European Journal of Operational Research, Elsevier, vol. 141(3), pages 689-698, September.
    7. Panagiotidou, Sofia & Tagaras, George, 2007. "Optimal preventive maintenance for equipment with two quality states and general failure time distributions," European Journal of Operational Research, Elsevier, vol. 180(1), pages 329-353, July.
    8. Ahmadi, Reza & Fouladirad, Mitra, 2017. "Maintenance planning for a deteriorating production process," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 108-118.
    9. Çekyay, Bora & Özekici, Süleyman, 2012. "Optimal maintenance of systems with Markovian mission and deterioration," European Journal of Operational Research, Elsevier, vol. 219(1), pages 123-133.
    10. Reza Ahmadi, 2014. "Optimal maintenance scheduling for a complex manufacturing system subject to deterioration," Annals of Operations Research, Springer, vol. 217(1), pages 1-29, June.
    11. C. Teresa Lam & R. H. Yeh, 1994. "Optimal replacement policies for multistate deteriorating systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(3), pages 303-315, April.
    12. Kivanç, İpek & Fecarotti, Claudia & Raassens, Néomie & van Houtum, Geert-Jan, 2024. "A scalable multi-objective maintenance optimization model for systems with multiple heterogeneous components and a finite lifespan," European Journal of Operational Research, Elsevier, vol. 315(2), pages 567-579.
    13. Ahmadi, Reza & Newby, Martin, 2011. "Maintenance scheduling of a manufacturing system subject to deterioration," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1411-1420.
    14. Panagiotidou, Sofia & Nenes, George, 2009. "An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 732-741.
    15. Kurt, Murat & Kharoufeh, Jeffrey P., 2010. "Optimally maintaining a Markovian deteriorating system with limited imperfect repairs," European Journal of Operational Research, Elsevier, vol. 205(2), pages 368-380, September.
    16. Ciriaco Valdez‐Flores & Richard M. Feldman, 1989. "A survey of preventive maintenance models for stochastically deteriorating single‐unit systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(4), pages 419-446, August.

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