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Dynamic availability analysis using dynamic Bayesian and evidential networks
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AI
DOI：10.1016/j.psep.2021.07.003.png)
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Abstract
En 中文
The probabilistic modelling is widely used in engineering practices, especially for assessing the safety and reliability of complex systems. Dynamic evidential network (DEN) can efficiently deal with epistemic uncertainty based on Dempster-Shafer theory. This work proposes an extended discrete-time DEN model along with an extensive review of its applications in engineering. The proposed model combines the Dempster-Shafer theory, used for handling epistemic uncertainty across a new state-space reconstruction of components, and the dynamic Bayesian network is used for multi-state system reliability. The model application is demonstrated on a real case study from the aviation field. The application quantifies reliability and availability parameters that help to prioritize maintenance activities and avoid failures of complex redundant systems. The proposed model can serve as a tool to assess the reliability and availability of industrial systems suffering from parameter uncertainty and common cause failures. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords:
Evidence theory
Evidential network
Common cause failure
Parameter uncertainty
Dempster-Shafer theory
Availability
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