Manuscript Title:

FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HSE IN OIL AND GAS INDUSTRY

Author:

SHUAIB KAKA, HILMI HUSSIN, RANO KHAN, ALI AKBAR, UMAIR SARWAR, JANSHER ANSARI

DOI Number:

DOI:10.17605/OSF.IO/WVG2H

Published : 2022-06-10

About the author(s)

1. SHUAIB KAKA - Department of Industrial Engineering and Management, Dawood University of Engineering and Technology, Karachi, Pakistan.
2. HILMI HUSSIN - Department of Mechanical Engineering, Universiti Teknologi PETRONAS (UTP), Bandar Seri Iskandar, Seri Iskandar, Perak, Malaysia.
3. RANO KHAN - Department of Industrial Engineering and Management, Dawood University of Engineering and Technology, Karachi, Pakistan.
4. ALI AKBAR - Department of Industrial Engineering and Management, Dawood University of Engineering and Technology, Karachi, Pakistan.
5. UMAIR SARWAR - Department of Industrial Engineering and Management, Dawood University of Engineering and Technology, Karachi, Pakistan.
6. JANSHER ANSARI - Department of Industrial Engineering and Management, Dawood University of Engineering and Technology, Karachi, Pakistan.

Full Text : PDF

Abstract

The qualitative risk matrix is used in oil and gas industries to evaluate hazard risk related to health, safety, and environment (HSE). Traditional risk matrix processes may enhance the uncertainties in assessing the crucial factors regarding HSE. A better technique is needed to develop in order to overcome these uncertainties. Thus, this study has developed the Fuzzy Logic-Based Quantitative Risk Assessment (FLQRA) model to more accurately assess the HSE risks. In this approach, experts (decision-makers) provide their priority of risk assessment information for the severity of consequences and likelihood of HSE classifications in numerical scaling. Afterward, using a combination of consequence and likelihood associated with each category, the Fuzzy Logic approach is utilized to assess the risk level. MATLABTM software is used to construct a Graphical User Interface (GUI) model to estimate the quantitative risk level, ranking, and priority for HSE categories according to the calculated risk scores for single and multi-expert inputs. Moreover, the weighted average factor is also introduced to measure the efficiency of experience of the expert in the final risk ranking. The effectiveness of the proposed FLQRA model is evaluated by three different case studies and the results from the model are compared with the existing method. FLQRA model has demonstrated to have the capability to facilitate decision-makers in evaluating the risk involved with HSE in oil and gas industry more effectively.


Keywords

Quantitative risk assessment, graphical user interface, fuzzy logic.