A dynamic prescriptive maintenance model considering system aging and degradation

Bin Liu; Jing Lin; Liangwei Zhang; Uday Kumar

doi:10.1109/ACCESS.2019.2928587

A dynamic prescriptive maintenance model considering system aging and degradation

Bin Liu, Jing Lin, Liangwei Zhang^*, Uday Kumar

^*Corresponding author for this work

Management Science

Research output: Contribution to journal › Article › peer-review

37 Citations (Scopus)

58 Downloads (Pure)

Abstract

This paper develops a dynamic maintenance strategy for a system subject to aging and degradation. The influence of degradation level and aging on system failure rate is modeled in an additive way. Based on the observed degradation level at the inspection, repair or replacement is carried out upon the system. Previous researches assume that repair will always lead to an improvement in the health condition of the system. However, in our study, repair reduces the system age but on the other hand, increases the degradation level. Considering the two-fold influence of maintenance actions, we perform reliability analysis on system reliability as a first step. The evolution of system reliability serves as a foundation for establishing the maintenance model. The optimal maintenance strategy is achieved by minimizing the long-run cost rate in terms of the repair cycle. At each inspection, the parameters of the degradation processes are updated with maximum a posteriori estimation when a new observation arrives. The effectiveness of the proposed model is illustrated through a case study of locomotive wheel-sets. The maintenance model considers the influence of degradation and aging on system failure and dynamically determines the optimal inspection time, which is more flexible than traditional stationary maintenance strategies and can provide better performance in the field.

Original language	English
Article number	8762155
Pages (from-to)	94931-94943
Number of pages	13
Journal	IEEE Access
Volume	7
DOIs	https://doi.org/10.1109/ACCESS.2019.2928587
Publication status	Published - 15 Jul 2019

Funding

This work was supported in part by the Luleå Railway Research Centre (Järnvägstekniskt Centrum), Sweden, in part by the Swedish Transport Administration (Trafikverket), in part by a project by the NSFC under Grant 71801045, and in part by the Youth Innovative Talent Project from the Department of Education of Guangdong Province, China, under Grant 2017KQNCX191.

Keywords

aging and degradation process
dynamic maintenance strategy
locomotive wheel-sets
prescriptive maintenance
sequential schedule

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10.1109/ACCESS.2019.2928587Licence: CC BY 4.0

Liu-etal-IEEEA2019-A-dynamic-prescriptive-maintenance-model-considering-systemFinal published version, 10.7 MBLicence: CC BY 4.0

Cite this

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title = "A dynamic prescriptive maintenance model considering system aging and degradation",

abstract = "This paper develops a dynamic maintenance strategy for a system subject to aging and degradation. The influence of degradation level and aging on system failure rate is modeled in an additive way. Based on the observed degradation level at the inspection, repair or replacement is carried out upon the system. Previous researches assume that repair will always lead to an improvement in the health condition of the system. However, in our study, repair reduces the system age but on the other hand, increases the degradation level. Considering the two-fold influence of maintenance actions, we perform reliability analysis on system reliability as a first step. The evolution of system reliability serves as a foundation for establishing the maintenance model. The optimal maintenance strategy is achieved by minimizing the long-run cost rate in terms of the repair cycle. At each inspection, the parameters of the degradation processes are updated with maximum a posteriori estimation when a new observation arrives. The effectiveness of the proposed model is illustrated through a case study of locomotive wheel-sets. The maintenance model considers the influence of degradation and aging on system failure and dynamically determines the optimal inspection time, which is more flexible than traditional stationary maintenance strategies and can provide better performance in the field.",

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A dynamic prescriptive maintenance model considering system aging and degradation

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