Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks

Papadopoulos, Yiannis; Walker, Martin; Kabir, Sohag

Abstract

© 2018 Elsevier Ltd Dynamic systems exhibit time-dependent behaviours and complex functional dependencies amongst their components. Therefore, to capture the full system failure behaviour, it is not enough to simply determine the consequences of different combinations of failure events: it is also necessary to understand the order in which they fail. Pandora temporal fault trees (TFTs) increase the expressive power of fault trees and allow modelling of sequence-dependent failure behaviour of systems. However, like classical fault tree analysis, TFT analysis requires a lot of manual effort, which makes it time consuming and expensive. This in turn makes it less viable for use in modern, iterated system design processes, which requires a quicker turnaround and consistency across evolutions. In this paper, we propose for a model-based analysis of temporal fault trees via HiP-HOPS, which is a state-of-the-art model-based dependability analysis method supported by tools that largely automate analysis and optimisation of systems. The proposal extends HiP-HOPS with Pandora, Petri Nets and Bayesian Networks and results to dynamic dependability analysis that is more readily integrated into modern design processes. The effectiveness is demonstrated via application to an aircraft fuel distribution system.

• Journal Article Type: Article
• Publication Date: Jun 1, 2018
• Journal: Safety science
• Print ISSN: 0925-7535
• Electronic ISSN: 1879-1042
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 105
• Pages: 55-70
• APA6 Citation: Papadopoulos, Y., Walker, M., & Kabir, S. (2018). Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks. Safety science, 105, 55-70. https://doi.org/10.1016/j.ssci.2018.02.001
• DOI: https://doi.org/10.1016/j.ssci.2018.02.001
• Keywords: Fault tree analysis; Reliability analysis; Model-based safety analysis; Dynamic fault trees; Temporal fault trees; HiP-HOPS; Petri nets, Bayesian networks; Public health; Environmental and occupational health; Safety research; Safety, risk, reliability an
• Publisher URL: https://www.journals.elsevier.com/safety-science/
• Copyright Statement: ©2018, Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
• Additional Information: This article is maintained by: Elsevier; Article Title: Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks; Journal Title: Safety Science; CrossRef DOI link to publisher maintained version: http://dx.doi.org/10.1016/j.ssci.2018.02.001; Content Type: article; Copyright: © 2018 Elsevier Ltd. All rights reserved.