A Framework for Risk Assessment in Oil and Gas Supply Chains
Author URLs
Document Type
Conference Proceeding
Publication Date
5-2016
Subject: LCSH
Business logistics, Petroleum, Natural gas
Disciplines
Engineering Education | Operations Research, Systems Engineering and Industrial Engineering
Abstract
The use of simulation models as decision-support tools in supply chain risk management has been motivated by the need for powerful risk and reliability analysis models. Conventional computer supported reliability analysis, such as fault tree analysis and event tree analysis, are commonly used. However, these tools alone might not be able to capture all the dimensions of the system. Discrete-Event Simulation (DES) can be used as a comprehensive reliability and risk analysis tool that can capture the dynamic interactions of system components. In this paper, we assess the vulnerability of oil and gas supply chains to disruption and operational risks and measure the impact on customer satisfaction and inventory levels. A Continuous-Time Discrete-Event (CTDE) simulation model is constructed for an oil and gas supply chain to capture the flow of material through the supply chain. A Bow-Tie analysis is then developed through DES to understand the dynamic nature of the risks and measure their impact. The results obtained from the case study under consideration indicated that reducing the time-to-recover is a better mitigation strategy compared to increasing the capacity for gradual recovery.
Repository Citation
Erdil, Nadiye O.; Kbah, Zaid; and Aqlan, Faisal, "A Framework for Risk Assessment in Oil and Gas Supply Chains" (2016). Engineering and Applied Science Education Faculty Publications. 6.
https://digitalcommons.newhaven.edu/sgiengineering-facpubs/6
Publisher Citation
Erdil, Nadiye PhD, Kbah Zaid, Aqlan, Faisal. (2016) A Framework for Risk Assessment in Oil and Gas Supply Chains. H. Yang, Z. Kong, and MD Sarder, eds. Proceedings of the 2016 Industrial and Systems Engineering Research Conference, Anaheim, CA, May 21-24, 2016.
Comments
(C) 2016 IISE. All rights reserved.