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A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure

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  • Wang, Ling
  • Chu, Jian
  • Mao, Weijie

Abstract

A new policy, referred to as the condition-based replacement and spare provisioning policy, is presented for deteriorating systems with a number of identical units. It combines the condition-based replacement policy with periodical inspections and the (S,s) type inventory policy, noted as the (T,S,s,Lp) policy, where T is the inspection interval, S is the maximum stock level, s is the reorder level, and Lp is the preventive replacement threshold for the deterioration levels of units. The deterioration level of each unit in the system can be described by a scalar random variable, which is continuous and increasing monotonically. Furthermore, the deterioration level just when the unit failure occurs, termed deterioration to failure, is uncertain. Therefore, the condition-based reliability is proposed in order to characterize various and uncertain deterioration levels when unit failure occurs. A simulation model is developed for the system operation under the proposed condition-based replacement and spare provisioning policy. Thus, via the simulation method and the genetic algorithm, the decision variables T, S, s, and Lp can be jointly optimized for minimizing the cost rate. A case study is given, showing the procedure of applying the proposed policy and the condition-based reliability methodology to optimizing the maintenance scheme of haul truck motors at a mine site based on oil inspections, and proving beneficial for plant maintenance managers to reduce maintenance cost.

Suggested Citation

  • Wang, Ling & Chu, Jian & Mao, Weijie, 2009. "A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure," European Journal of Operational Research, Elsevier, vol. 194(1), pages 184-205, April.
  • Handle: RePEc:eee:ejores:v:194:y:2009:i:1:p:184-205
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    References listed on IDEAS

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