This thesis proposes a discrete event simulation model to investigate the complex interactions among supply chain components and infrastructure (1) under normal conditions when the facility can maintain the continuity of its performance under uncertainty and (2) under disruption scenarios. The model shows the flow of the risk in the supply chain. A special focus is given to risks from both (1) the reliability of infrastructure affecting materials necessary to produce a final product and (2) failures of infrastructure that support the transportation of materials. Bayesian network provides necessary models to analyze the different types of infrastructure supporting the supply chain, including dependencies, in simplified terms. This thesis provides a quantitative assessment of supply chain resilience to characterize the impact of events that threaten supply chains due to uncertainty in infrastructure performance, including potential infrastructure failures. Results were used to demonstrate the development of mitigation plans to reduce the impact of infrastructure disruption on the supply chain to overcome the possible risks associated with infrastructure failure.