A dynamic prescriptive maintenance model considering system aging and degradation

Liu, Bin and Lin, Jing and Zhang, Liangwei and Kumar, Uday (2019) A dynamic prescriptive maintenance model considering system aging and degradation. IEEE Access, 7. pp. 94931-94943. 8762155. ISSN 2169-3536 (https://doi.org/10.1109/ACCESS.2019.2928587)

[thumbnail of Liu-etal-IEEEA2019-A-dynamic-prescriptive-maintenance-model-considering-system]
Preview
Text. Filename: Liu_etal_IEEEA2019_A_dynamic_prescriptive_maintenance_model_considering_system.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (11MB)| Preview

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.

ORCID iDs

Liu, Bin ORCID logoORCID: https://orcid.org/0000-0002-3946-8124, Lin, Jing, Zhang, Liangwei and Kumar, Uday;