A case study on fuzzy logic-based risk assessment in oil and gas industry

Risk assessment is a process of categorizing and measurement of risk related outcomes from a specific incident and in a particular scenario. While risk itself is considered as the combination of likelihood and severity of the consequences of hazards. Typically, the qualitative approach of risk based...

Full description

Saved in:
Bibliographic Details
Main Authors: Hussin, H., Shuaib, K., Abd Majid, M.A.
Format: Article
Published: Asian Research Publishing Network 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961564455&partnerID=40&md5=a6b387b2e87cf71353c9d921181cda7a
http://eprints.utp.edu.my/25584/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.25584
record_format eprints
spelling my.utp.eprints.255842021-08-27T09:59:30Z A case study on fuzzy logic-based risk assessment in oil and gas industry Hussin, H. Shuaib, K. Abd Majid, M.A. Risk assessment is a process of categorizing and measurement of risk related outcomes from a specific incident and in a particular scenario. While risk itself is considered as the combination of likelihood and severity of the consequences of hazards. Typically, the qualitative approach of risk based inspection (RBI) is applied in oil and gas industries to measure the risk levels of hazards. But with this qualitative approach sometime the risk ranking ties among the different factors can lead to problem in selecting the most critical factor. To address the problem, this study aims to develop a fuzzy logic-base risk assessment model using a quantitative approach of RBI that will assist to mitigate the risk ties in risk ranking process of hazard. In this proposed model, fuzzy membership functions and ranges have been assigned for likelihood, severity of consequences and for total risk levels. A case study on ammonia hazard is presented to demonstrate the vitality of the proposed fuzzy risk assessment model with samples of four categories (people, environment, asset and reputation) from an oil and gas industry. The outcomes of this study indicate that the developed model has a strong potential application in oil and gas industry in assessing the severity levels of risk, and resolving risk ranking ties. © 2006-2016 Asian Research Publishing Network (ARPN). Asian Research Publishing Network 2016 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961564455&partnerID=40&md5=a6b387b2e87cf71353c9d921181cda7a Hussin, H. and Shuaib, K. and Abd Majid, M.A. (2016) A case study on fuzzy logic-based risk assessment in oil and gas industry. ARPN Journal of Engineering and Applied Sciences, 11 (5). pp. 3049-3054. http://eprints.utp.edu.my/25584/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Risk assessment is a process of categorizing and measurement of risk related outcomes from a specific incident and in a particular scenario. While risk itself is considered as the combination of likelihood and severity of the consequences of hazards. Typically, the qualitative approach of risk based inspection (RBI) is applied in oil and gas industries to measure the risk levels of hazards. But with this qualitative approach sometime the risk ranking ties among the different factors can lead to problem in selecting the most critical factor. To address the problem, this study aims to develop a fuzzy logic-base risk assessment model using a quantitative approach of RBI that will assist to mitigate the risk ties in risk ranking process of hazard. In this proposed model, fuzzy membership functions and ranges have been assigned for likelihood, severity of consequences and for total risk levels. A case study on ammonia hazard is presented to demonstrate the vitality of the proposed fuzzy risk assessment model with samples of four categories (people, environment, asset and reputation) from an oil and gas industry. The outcomes of this study indicate that the developed model has a strong potential application in oil and gas industry in assessing the severity levels of risk, and resolving risk ranking ties. © 2006-2016 Asian Research Publishing Network (ARPN).
format Article
author Hussin, H.
Shuaib, K.
Abd Majid, M.A.
spellingShingle Hussin, H.
Shuaib, K.
Abd Majid, M.A.
A case study on fuzzy logic-based risk assessment in oil and gas industry
author_facet Hussin, H.
Shuaib, K.
Abd Majid, M.A.
author_sort Hussin, H.
title A case study on fuzzy logic-based risk assessment in oil and gas industry
title_short A case study on fuzzy logic-based risk assessment in oil and gas industry
title_full A case study on fuzzy logic-based risk assessment in oil and gas industry
title_fullStr A case study on fuzzy logic-based risk assessment in oil and gas industry
title_full_unstemmed A case study on fuzzy logic-based risk assessment in oil and gas industry
title_sort case study on fuzzy logic-based risk assessment in oil and gas industry
publisher Asian Research Publishing Network
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961564455&partnerID=40&md5=a6b387b2e87cf71353c9d921181cda7a
http://eprints.utp.edu.my/25584/
_version_ 1738656750707408896
score 13.211869