Yes / System safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches
are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include,
but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event
Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically
make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive
and accurate analysis of complex systems, different characteristics such as functional dependencies among
components, temporal behaviour of systems, multiple failure modes/states for components/systems, and
uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical
approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity
in risk assessment applications due to their flexible structure and capability of incorporating most of the
above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis.
Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic
behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This
paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability
and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over
other classical approaches, and relative strengths and weaknesses in different practical application scenarios. / This work was funded by the DEIS H2020 project (Grant Agreement 732242).
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/17427 |
| Date | 18 October 2019 |
| Creators | Kabir, Sohag, Papadopoulos, Y. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2019 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license. |
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