Loughney, S and Wang, J (2017) Bayesian network modelling of an offshore electrical generation system for applications within an asset integrity case for normally unattended offshore installations. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 232 (4). ISSN 1475-0902

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Abstract

This article proposes the initial stages of the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore system. The main focus is the construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity. The majority of the data required to complete the Bayesian network was gathered from various databases and past risk assessment experiments and projects. However, where data were incomplete or non-existent, expert judgement was applied through pairwise comparison, analytical hierarchy process and a symmetric method to fill these data gaps and to complete larger conditional probability tables. A normally unattended installation–Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed to ensure safe operations in situations whereby physical human-to-machine interaction is not occurring. The Integrity Case can be said to be dynamic as it shall be continually updated for an installation as the quantitative risk analysis data are recorded. This allows for the integrity of the various systems and components of an offshore installation to be continually monitored. The Bayesian network allows cause and effect relationships to be modelled through clear graphical representation. The model accommodates for continual updating of failure data.

Item Type:	Article
Uncontrolled Keywords:	0911 Maritime Engineering, 0915 Interdisciplinary Engineering
Subjects:	T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions:	Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher:	SAGE Publications
Date Deposited:	14 Mar 2018 11:34
Last Modified:	04 Sep 2021 10:47
DOI or ID number:	10.1177/1475090217704787
URI:	https://researchonline.ljmu.ac.uk/id/eprint/7988

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