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A proactive approach to quantitative assessment of disruption risks of petroleum refinery operation

Ishola, A, Matellini, DB and Wang, J (2020) A proactive approach to quantitative assessment of disruption risks of petroleum refinery operation. Safety Science, 127. ISSN 0925-7535

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Abstract

Petroleum refinery consists of numerous process units in operation, which are subjected to diverse accident risks in day-to-day operations under extreme operating conditions. Due to the complexity of petroleum refinery operations, any failure can lead to major accident and a huge financial loss for a petroleum refining company. However, petroleum refinery operations can be disrupted by various risk elements from the organization, technical, operational and external latent conditions. Risk elements are often inherent in operations, which can be based on uncertain knowledge, oversight and lack of perception of interactive events that can lead to disruption. In order to circumvent events that can cause disruption in a petroleum refinery, the criticality of the risk elements and their attributes that are associated with Petroleum Refinery Process Units (PRPU) operations need to be investigated. Therefore, there is a need to identify and assess the most critical risk elements and attributes that can interact to cause the disruption of operational reliability and availability of a petroleum refinery process unit. Hence, this article proposes a robust fuzzy linguistic assessment methodology for identification and assessment of PRPU risk elements and their attributes. The methodology deals with the main challenges of utilising expert's subjective judgements, in terms of the assessment of PRPU risk elements under uncertain situations. The result of the evaluation and ranking of PRPU risk elements and their attributes can provide salient risk information to duty holders and decision makers in the petroleum refinery in order to prioritise resources for risk management of the most critical attributes of the risk elements. © 2020 Elsevier Ltd

Item Type: Article
Uncontrolled Keywords: 09 Engineering, 11 Medical and Health Sciences, 17 Psychology and Cognitive Sciences
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
T Technology > T Technology (General)
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher: Elsevier
Date Deposited: 12 May 2020 10:46
Last Modified: 12 May 2020 10:46
DOI or Identification number: 10.1016/j.ssci.2020.104666
URI: https://researchonline.ljmu.ac.uk/id/eprint/12736

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