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An integrated modelling framework for complex systems safety analysis

Tolo, Silvia; Andrews, John

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Authors

SILVIA TOLO SILVIA.TOLO@NOTTINGHAM.AC.UK
Research Fellowship

JOHN ANDREWS john.andrews@nottingham.ac.uk
Professor of Infrastructure Asset Management



Abstract

The ever-increasing complexity of engineering systems has fuelled the need for novel and efficient computational tools able to enhance the accuracy of current modelling strategies for industrial systems. Indeed, traditional Fault and Event Tree techniques still monopolize the reliability analysis of complex systems despite their limitations, such as the inability to capture underlying dependencies between components or to include degradation processes and complex maintenance strategies into the analysis. However, the lack of alternative solutions able to tackle large-scale modelling efficiently has contributed to the continued use of such methodologies, together with their robustness and familiarity well rooted in engineering practice. The current paper defines a novel modelling framework for safety system performance which retains the capabilities of both fault and event tree methods, but also overcomes their limitations. The ambition is to provide a technique for application to real-world systems preserving a familiar user–model interface and grounding the novel approach in well-known and established reliability techniques. In order to describe the methodology developed and demonstrate its validity, five case-studies referring to a simplified industrial plant cooling system are analysed and discussed. Further discussion regarding the scalability of the proposed approach is provided, outlining the advantages of the current implementation and its computationalcost.

Citation

Tolo, S., & Andrews, J. (2022). An integrated modelling framework for complex systems safety analysis. Quality and Reliability Engineering International, 38(8), 4330-4350. https://doi.org/10.1002/qre.3212

Journal Article Type Article
Acceptance Date Sep 8, 2022
Online Publication Date Oct 11, 2022
Publication Date 2022-12
Deposit Date Sep 21, 2022
Publicly Available Date Oct 12, 2023
Journal Quality and Reliability Engineering International
Print ISSN 0748-8017
Electronic ISSN 1099-1638
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 38
Issue 8
Pages 4330-4350
DOI https://doi.org/10.1002/qre.3212
Keywords Management Science and Operations Research; Safety, Risk, Reliability and Quality
Public URL https://nottingham-repository.worktribe.com/output/11467309
Publisher URL https://onlinelibrary.wiley.com/doi/10.1002/qre.3212

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