Examining Critical Material Supply Chains Through a Bayesian Network Model

The United States economic and national security sectors remain vulnerable to shortages of critical materials due to the risks posed by disruptions in globally-dispersed supply networks. Numerous methods over the past 10 years have been proposed to identify, assess, and evaluate risks in critical material supply chains. This praxis provides a method to quantify the impact of supply disruptions and inform the application of risk mitigation measures for a critical material supply chain from mineral deposits to final platform. It proposes a Bayesian network modeling method not yet applied to the problem in publicly available studies and fits with an assessment methodology proposed by the National Science and Technology Center (NSTC). Results from this study provide indicative answers to how supply disruptions propagate through a selected critical material supply network, which nodes are vulnerable to supply disruptions, and whether mitigating actions can reduce the impact of supply disruptions. The approach here demonstrates that a Bayesian network model can be one of the tools in a criticality assessment methodology.

Author

• Kling, Joseph

Language

• en

Keyword

• Bayesian networks
• Supply chain risk management
• Applied sciences
• Critical materials
• Engineering management
• Supply risk

Date created

• 2018

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Engineering Management

Degree

• D.Engr.

Advisor

• Tozer, Bentz
• Jarvandi, Ali

Committee Member(s)

• Etemadi, Amirhossein
• Malalla, Ebrahim
• Carroll, Adam

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/70795779p