Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.733973
Title: Advanced safety methodology for risk management of petroleum refinery operations
Author: Ishola, A.
ISNI:       0000 0004 6496 7990
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 2018
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Abstract:
Petroleum refineries are important facilities for refining petroleum products that provide the primary source of energy for domestic and industrial consumption globally. Petroleum refinery operations provide significant contribution to global economic growth. Petroleum refineries are complex, multifaceted systems that perform multiple phase operations characterized by a high level of risk. Evidence based major accidents that have occurred within the last three decades in the petroleum refineries, around the world, indicates losses estimated in billions of US dollars. Many of these accidents are catastrophes, which have led to the disruption of petroleum refinery operations. These accidents have resulted in production loss, asset damage, environmental damage, fatalities and injuries. However, the foremost issue analysed in literatures in relation to major accidents in petroleum refineries, is the lack of robust risk assessment and resourceful risk management approaches to identify and assess major accident risks, in order to prevent or mitigate them from escalating to an accident. Thus, it is exceptionally critical to readdress the issue of petroleum refinery risk management with the development of a more dependable, adaptable and holistic risk modelling framework for major accident risks investigation. In this thesis, a proactive framework for advanced risk management to analyse and mitigate the disruption risks of petroleum refinery operations is presented. In this research, various risk elements and their attributes that can interact to cause the disruption of PRPU operations were identified and analysed, in order to determine their criticality levels. This thesis shows that the convergent effect of the interactions between the risk elements and their attributes can lead to the disruption of petroleum refinery operations. In the scheme of the study, Fuzzy Linguistic Preference Relation (FLPR), Fuzzy Evidential Reasoning (FER) and Fuzzy Bayesian Network (FBN) methodologies were proposed and implemented to evaluate the criticality of the risk elements and their attributes and to analyse the risk level of PRPU operations. Also, AHP-fuzzy VIKOR methodology was utilised for decision modelling to determine the optimal strategy for the risk management of the most significant risk elements’ attributes that can interact to cause the disruption of PRPU operations. The methodologies proposed and implemented in this research can be utilised in the petroleum refining industry, to analyse complex risk scenarios where there is incomplete information concerning risk events or where the probability of risk events is uncertain. The result of the analysis conducted in this research to determine the risk level of petroleum refinery operations can be utilised by risk assessors and decision makers as a threshold value for decision making in order to mitigate the disruption risk of PRPU operations. The decision strategies formulated in this thesis based on robust literature review and expert contributions, contributes to knowledge in terms of the risk management of petroleum refinery operations. The result of the evaluation and ranking of the risk elements and their attributes can provide salient risk information to duty holders and decision makers to improve their perceptions, in order to prioritise resources for risk management of the most critical attributes of the risk elements. Overall, the methodologies applied in this thesis, can be tailored to be utilised as a quantitative risk assessment tool, by risk managers and decision analysts in the petroleum refining industry for enhancement risk assessment processes where available information can sometimes be vague or incomplete for risk analysis.
Supervisor: Matellini, D. B. ; Wang, J. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.733973  DOI:
Keywords: TA Engineering (General). Civil engineering (General) ; TP Chemical technology
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