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A Discrete Maintenance and Replacement Model under Technological Breakthrough Expectations

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  • Abraham Mehrez
  • Gad Rabinowitz
  • Eli Shemesh

Abstract

Two cases of the discrete time finite horizon technology replacement problem are solved. The first deals with two available machines, one in use and a better one that can be purchased to replace it. The second case considers, in addition, a third machine of future technology that will be available at some random future time. The maintenance level of each used machine is chosen for each period in order to economically control performance deterioration. For solving the model, we first derive an optimal preventive maintenance policy by showing that “bang-bang” (i.e., full or non), non-increasing, maintenance efforts are optimal. Employing the optimal maintenance policy, we reformat the problem and conduct a numerical search in order to derive the replacement policy that will maximize the expected net present profit. Numerical examples demonstrate that management may improve profitability by delaying (but not necessarily foregoing) replacement with an available better machine. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Abraham Mehrez & Gad Rabinowitz & Eli Shemesh, 2000. "A Discrete Maintenance and Replacement Model under Technological Breakthrough Expectations," Annals of Operations Research, Springer, vol. 99(1), pages 351-372, December.
    • Handle: RePEc:spr:annopr:v:99:y:2000:i:1:p:351-372:10.1023/a:1019236203575
    DOI: 10.1023/A:1019236203575
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    Citations

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    Cited by:

    1. Natali Hritonenko & Yuri Yatsenko, 2012. "Fleet replacement under technological shocks," Annals of Operations Research, Springer, vol. 196(1), pages 311-331, July.
    2. A. Bensoussan & Q. Feng & S. P. Sethi, 2022. "Integrating equipment investment strategy with maintenance operations under uncertain failures," Annals of Operations Research, Springer, vol. 317(2), pages 353-386, October.
    3. Ali Dogramaci & Nelson M. Fraiman, 2004. "Replacement Decisions with Maintenance Under Uncertainty: An Imbedded Optimal Control Model," Operations Research, INFORMS, vol. 52(5), pages 785-794, October.
    4. Sendstad, Lars Hegnes & Chronopoulos, Michail, 2020. "Sequential investment in renewable energy technologies under policy uncertainty," Energy Policy, Elsevier, vol. 137(C).
    5. Öner, K.B. & Kiesmüller, G.P. & van Houtum, G.J., 2015. "On the upgrading policy after the redesign of a component for reliability improvement," European Journal of Operational Research, Elsevier, vol. 244(3), pages 867-880.

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