Maintenance-based prognostics of nuclear plant equipment for long-term operation

While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, the...

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Bibliographic Details
Published in:Nuclear engineering and technology 2017, 49(5), , pp.914-919
Main Authors: Welz, Zachary, Coble, Jamie, Upadhyaya, Belle, Hines, Wes
Format: Article
Language:English
Subjects:
Maintenance
Predictive
Prognostics
Reliability
Repair
Sustainability
원자력공학
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Summary:While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, these models assume that all maintenance actions are the same or do not consider maintenance at all. This study investigates the influence of integrating maintenance information on prognostic model prediction accuracy. By incorporating maintenance information to develop maintenance-dependent prognostic models, prediction accuracy was improved by more than 40% compared with traditional maintenance-independent models. This study acts as a proof of concept, showing the importance of utilizing maintenance information in modern prognostics for industrial equipment.
ISSN:1738-5733
2234-358X
DOI:10.1016/j.net.2017.06.001