FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY

Several approaches of risk assessment process like; qualitative, quantitative and semi-quantitative approaches are used to mitigate the risk level of hazards. Typically, in oil and gas industry, the qualitative risk matrix is applied for evaluating the risk assessment of hazards related to health, s...

Full description

Saved in:
Bibliographic Details
Main Author: KAKA, SHUAIB
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://utpedia.utp.edu.my/18398/1/Shuaib%20Kaka%20%28G02807%29.pdf
http://utpedia.utp.edu.my/18398/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utp-utpedia.18398
record_format eprints
spelling my-utp-utpedia.183982019-01-28T13:29:42Z http://utpedia.utp.edu.my/18398/ FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY KAKA, SHUAIB TJ Mechanical engineering and machinery Several approaches of risk assessment process like; qualitative, quantitative and semi-quantitative approaches are used to mitigate the risk level of hazards. Typically, in oil and gas industry, the qualitative risk matrix is applied for evaluating the risk assessment of hazards related to health, safety, and environment (HSE). The existing qualitative risk matrix process may increase the uncertainty to select the critical factors of HSE categories; People, Environment, Asset, and Reputation. In order to overcome this uncertainty, a better approach needs to be developed. The objective of this research is to develop a Fuzzy Logic-Based Quantitative Risk Assessment (FLQRA) model to assess HSE risks more accurately. In this model, decision makers (experts) provide their preference of risk assessment information for severity of consequence and likelihood of HSE categories in numerical scaling. Then the Fuzzy Logic method is used to evaluate the risk level with the combination of consequence and likelihood associated to each category. To develop the model different type of Fuzzy Inference methods; Mamdani and Sugeno Inference System and different types of membership functions are used to generate the results and are compared with the existing method results. 2018-06 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/18398/1/Shuaib%20Kaka%20%28G02807%29.pdf KAKA, SHUAIB (2018) FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
KAKA, SHUAIB
FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
description Several approaches of risk assessment process like; qualitative, quantitative and semi-quantitative approaches are used to mitigate the risk level of hazards. Typically, in oil and gas industry, the qualitative risk matrix is applied for evaluating the risk assessment of hazards related to health, safety, and environment (HSE). The existing qualitative risk matrix process may increase the uncertainty to select the critical factors of HSE categories; People, Environment, Asset, and Reputation. In order to overcome this uncertainty, a better approach needs to be developed. The objective of this research is to develop a Fuzzy Logic-Based Quantitative Risk Assessment (FLQRA) model to assess HSE risks more accurately. In this model, decision makers (experts) provide their preference of risk assessment information for severity of consequence and likelihood of HSE categories in numerical scaling. Then the Fuzzy Logic method is used to evaluate the risk level with the combination of consequence and likelihood associated to each category. To develop the model different type of Fuzzy Inference methods; Mamdani and Sugeno Inference System and different types of membership functions are used to generate the results and are compared with the existing method results.
format Thesis
author KAKA, SHUAIB
author_facet KAKA, SHUAIB
author_sort KAKA, SHUAIB
title FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
title_short FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
title_full FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
title_fullStr FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
title_full_unstemmed FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY
title_sort fuzzy logic-based quantitative risk assessment model for health safety and environment in oil and gas industry
publishDate 2018
url http://utpedia.utp.edu.my/18398/1/Shuaib%20Kaka%20%28G02807%29.pdf
http://utpedia.utp.edu.my/18398/
_version_ 1739832499102547968
score 13.18916