Fault Tree Analysis Including Component Dependencies

Tolo, Silvia; Andrews, John

Abstract

Fault Tree analysis is not only the most common technique used in engineering practice for the estimation of system reliability, but is also a key tool shared between designers, analysts and regulators for safe operation and licensing purposes. In spite of its long lasting success, traditional Fault Tree analysis presents significant limitations in modelling a wide range of features frequently encountered in modern systems. The most critical of these is the assumption of failure events independence, which is often not justified by the realistic behaviour of engineering system, undermining modelling accuracy. This paper introduces a novel methodology for the analysis of Fault Trees allowing for component dependencies and dynamic features. The proposed approach, based on the use of Binary Decision Diagrams, is demonstrated using a simple numerical application for verification. Its applicability and computational feasibility is discussed in details.

Citation

Tolo, S., & Andrews, J. (2024). Fault Tree Analysis Including Component Dependencies. IEEE Transactions on Reliability, 73(1), 413-421. https://doi.org/10.1109/TR.2023.3264943

• Journal Article Type: Article
• Acceptance Date: Mar 31, 2023
• Online Publication Date: Apr 19, 2023
• Publication Date: 2024-03
• Deposit Date: May 5, 2023
• Publicly Available Date: May 5, 2023
• Journal: IEEE Transactions on Reliability
• Print ISSN: 0018-9529
• Electronic ISSN: 1558-1721
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 73
• Issue: 1
• Pages: 413-421
• DOI: https://doi.org/10.1109/TR.2023.3264943
• Keywords: Probability , Reliability , Analytical models , Computational modeling , Binary decision diagrams , Estimation , Upper bound , dependency analysis , fault tree analysis , reliability engineering , risk analysis
• Public URL: https://nottingham-repository.worktribe.com/output/20286250
• Publisher URL: https://ieeexplore.ieee.org/document/10105629