4.7 Article

A maintenance strategy based on system reliability considering imperfect corrective maintenance and shocks

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 164, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2021.107886

Keywords

Maintenance; Reliability; Shocks; Optimization

Funding

  1. National Natural Science Foundation of China [71601086]
  2. Jiangsu Overseas Visiting Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents
  3. Major natural science fund for colleges and universities in Jiangsu province [19KJA140002]

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In this study, an innovative maintenance strategy is proposed to handle the normal degradation and shock process of systems. The strategy includes dividing the system reliability into different stages and implementing corresponding maintenance activities, as well as determining optimal control variables using the Particle Swarm Optimization algorithm. The proposed strategy is shown to be necessary and effective.
In this study, an innovative maintenance strategy is proposed for systems subject to normal degradation and shock process. The shock process is a non-homogeneous Poisson process, and a changing factor is considered for the dependence between the normal degradation and the occurrence intensity of shocks. The system reliability is divided into three stages, based on which maintenance activities are implemented. In Stage 1 and Stage 2, when a fatal shock occurs, corrective maintenance is performed if the number of completed corrective maintenance activities does not reach the allowed limit; Otherwise, the system is replaced. Replacement is always performed once the system reliability decreases to Stage 3. Corrective maintenance is imperfect, with a perfect or minimal effect at certain probabilities. Two control variables, the allowed numbers of corrective maintenance in Stage 1 and Stage 2, are determined to minimize the expected system cost rate, by using Particle Swarm Optimization algorithm. The proposed model and method are illustrated by an example of one sliding spool. The optimal result is verified by checking the results of feasible variables. Furthermore, the proposed maintenance policy is compared with two contrastive maintenance policies. The comparison results show the necessity and effectiveness of the proposed method.

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