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Research on maintenance decision-making approach based on dynamic opportunistic window

Baoshan Zhang, Guo Jilian, Zhou Zhangwen, Wang Xuan, Liu Xiaoxin

Eksploatacja i Niezawodność

2024

Vol. 26, no. 4

art. no. 191515

We have developed a maintenance decision-making approach based on dynamic opportunistic window (OW), utilizing algorithms such as k-mean clustering, expected maximum and parameter estimation to address the lack of a reasonable basis for the duration and divided number of OWs in current maintenance decision-making. Firstly, we have comprehensively summarized the multi-stage opportunistic maintenance (OM) decision-making approach, with a particular focus on its current strengths and limitations. Secondly, the modeling concept of the dynamic OW is analyzed, and the underlying assumptions are established. Furthermore, it elaborates on the theoretical foundation of the maintenance decision-making approach based on the dynamic OW through a detailed modeling process. Finally, we validate the proposed model by conducting experiments on tandem components from the main combustion chamber in an aero-engine. The experimental results demonstrate the significant value of the proposed maintenance decision-making approach based on dynamic OW in enhancing equipment reliability and optimizing maintenance support resources.