A sequential inspection and replacement policy for degradation-based systems

Zhicheng Zhu, Yisha Xiang, Suzan Alaswad, C. Richard Cassady

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Condition-based maintenance (CBM) has been extensively studied. However, the majority of existing CBM research either consider a periodic inspection schedule or a fixed preventive maintenance threshold. While policies with periodic inspections and/or fixed maintenance threshold are easy to implement in practice, they may incur more-than-necessary inspections and induce more failures. In this paper, we develop a sequential CBM policy for systems subject to stochastic degradation. The aim of the proposed policy is to prevent or delay failures and perform maintenance activities just in time. Unlike conventional preventive maintenance that often fixes the inspection interval and the preventive maintenance threshold, both the next inspection time and the corresponding maintenance threshold in this paper are dynamically determined based on the current state of the system. The proposed sequential predictive maintenance policy is particularly important and applicable for general non-homogeneous degradation processes. The proposed model enables optimal scheduling of inspection and preventive maintenance decisions, in order to minimize the long-run maintenance cost rate including inspection, preventive and corrective maintenance costs. The performance of the proposed predictive maintenance policy is evaluated using a simulation-based optimization approach. Frequency of system failures and total maintenance cost rates are computed and compared with a bench mark maintenance policy, a periodic inspection/replacement policy. Our results show that there can be potential savings from the proposed predictive maintenance policy.

Original languageEnglish
Title of host publication2017 Annual Reliability and Maintainability Symposium, RAMS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509052844
StatePublished - Mar 29 2017
Event2017 Annual Reliability and Maintainability Symposium, RAMS 2017 - Orlando, United States
Duration: Jan 23 2017Jan 26 2017

Publication series

NameProceedings - Annual Reliability and Maintainability Symposium
ISSN (Print)0149-144X


Conference2017 Annual Reliability and Maintainability Symposium, RAMS 2017
Country/TerritoryUnited States


  • Predictive maintenance
  • Simulation
  • Stochastic degradation


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