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Machine Replacement with Stochastic Costs

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  • Basil A. Kalymon

    (University of California, Los Angeles)

Abstract

The machine replacement model studied assumes that, at the end of each discrete interval, the state of deterioration of a machine and the current cost of replacement become known. A decision to keep or to replace must then be made, given that future deterioration and costs are determined by a known Markovian process. A finite set of possible states of deterioration is considered, including a "failed" state at which replacement by a "new" machine must occur. The operating cost is an increasing function of the level of deterioration, and replacement cost is the difference between new machine cost and salvage value. For both a finite and infinite planning horizon, given current cost, the optimality of a "control level" policy is demonstrated. Linear programming and policy iteration methods exploiting problem structure for the calculation of optimal policies are derived.

Suggested Citation

  • Basil A. Kalymon, 1972. "Machine Replacement with Stochastic Costs," Management Science, INFORMS, vol. 18(5-Part-1), pages 288-298, January.
    • Handle: RePEc:inm:ormnsc:v:18:y:1972:i:5-part-1:p:288-298
    DOI: 10.1287/mnsc.18.5.288
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    Cited by:

    1. 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.
    2. 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.

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