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A hybrid maintenance policy with fixed periodic structure and opportunistic replacement

Author

Listed:
  • Yan R Melo
  • Cristiano AV Cavalcante
  • Phil Scarf
  • Rodrigo S Lopes

Abstract

We model a maintenance policy with fixed periodic structure that is a hybrid of periodic inspection and opportunistic replacement. The policy is applicable to geographically remote systems such as offshore wind farms. The policy has three phases. Initially, there is an inspection phase to identify early defects. This is followed by a wear out phase during which corrective replacements are performed. Preventive replacement occurs at the end of this phase. The novelty of the model is an opportunistic phase, which overlaps with the latter part of the corrective phase, when preventive replacement is executed early if an opportunity arises. In this way, we model the reality in which remote systems with high logistics costs and restricted access may benefit from opportunistic visits for maintenance. Using a numerical example, we analyse the behaviour of the decision variables for a range of values of the parameters common to such systems. These parameters relate to: component heterogeneity; restricted access; default (failure to execute a planned action); arrival of opportunities and other standard parameters in a maintenance cost model. Specifically, our results indicate when opportunities can have a significant impact on the cost-rate of the optimum policy, but that leveraging opportunities cannot achieve a very high availability. Generally, we demonstrate that maintenance planning should be flexible when factors beyond the control of the maintainer impact maintenance effectiveness.

Suggested Citation

  • Yan R Melo & Cristiano AV Cavalcante & Phil Scarf & Rodrigo S Lopes, 2023. "A hybrid maintenance policy with fixed periodic structure and opportunistic replacement," Journal of Risk and Reliability, , vol. 237(3), pages 579-591, June.
  • Handle: RePEc:sae:risrel:v:237:y:2023:i:3:p:579-591
    DOI: 10.1177/1748006X221100365
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