Understanding, quantifying, and dealing with supply chain risk in energy sector necessitates the amalgamation of knowledge and techniques from several domains. Some of those domains are critical infrastructure analysis, risk analysis, systems simulation, geographic information systems, and supply chain management. The objective of this study is to develop a framework to explore and quantify risk of disruptions in the U.S. petroleum supply chain caused by natural disasters. The analysis is based on numerical and empirical data collected during Hurricanes Katrina and Rita. A semi- continuous simulation model of the petroleum supply chain is designed and implemented. A Geographic Information System (GIS) is employed for better management of spatial data. The Monte Carlo simulation at steady state is run with the inclusion of failure/recovery models for critical infrastructures. Output statistics representing key system performance measures and the status of infrastructure components are collected. Scenario outputs are compared and interpreted for their overall significance.
A Risk Analysis on the Continuity of the Petroleum Supply Chain
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Description
Understanding, quantifying, and dealing with supply chain risk in energy sector necessitates the amalgamation of knowledge and techniques from several domains. Some of those domains are critical infrastructure analysis, risk analysis, systems simulation, geographic information systems, and supply chain management. The objective of this study is to develop a framework to explore and quantify risk of disruptions in the U.S. petroleum supply chain caused by natural disasters. The analysis is based on numerical and empirical data collected during Hurricanes Katrina and Rita. A semi- continuous simulation model of the petroleum supply chain is designed and implemented. A Geographic Information System (GIS) is employed for better management of spatial data. The Monte Carlo simulation at steady state is run with the inclusion of failure/recovery models for critical infrastructures. Output statistics representing key system performance measures and the status of infrastructure components are collected. Scenario outputs are compared and interpreted for their overall significance.
Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for research attempting to explore risk analysis issues in supply chain management...
Risk Analysis, Assessment and Tools.- Supply Chain Risk Management - Developments, Issues and Challenges.- Assessing the Vulnerability of Supply Chains.- Risk Management in Value Networks.-...
Research Paper (postgraduate) from the year 2011 in the subject Business economics - Supply, Production, Logistics, grade: 5/5, Chalmers University of Technology Foundation Göteborg, language:...
"Supply Chain Risk Management is an issue that many companies face and yet few companies know how to deal with it in a systematic and pragmatic manner. While avoiding and reducing supply chain risks...
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