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A condition- and age-based replacement model using delay time modelling

Author

Listed:
  • T F Lipi
  • J-H Lim
  • M J Zuo
  • W Wang

Abstract

To make realistic maintenance decisions, it is important that maintenance managers make their preventive replacement decisions based on observations of the condition of their equipment. This study addresses a condition- and age-based replacement decision problem using the complete history of measured condition observations to minimize long-run average cost, maximize long-run average availability, or both. A stochastic filtering process (SFP) is used to estimate the residual lifetime distribution conditional on the history of observed condition information. A long-run average cost model and a long-run average availability model are analysed in order to determine the theorems necessary for calculating the optimum replacement time. To minimize the cost and maximize availability, a multiobjective decision frontier is proposed that will help maintenance managers deal with trade-offs between the two objectives. Finally, numerical examples are presented for each scenario to show the effectiveness of the methods proposed.

Suggested Citation

  • T F Lipi & J-H Lim & M J Zuo & W Wang, 2012. "A condition- and age-based replacement model using delay time modelling," Journal of Risk and Reliability, , vol. 226(2), pages 221-233, April.
    • Handle: RePEc:sae:risrel:v:226:y:2012:i:2:p:221-233
    DOI: 10.1177/1748006X11421265
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    References listed on IDEAS

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