The UNTD Faculty Speaker Series featured a discussion on the risk and resiliency of supply chains by Dr. Subhro Mitra, Associate Professor in the School of Business. I learned a great deal about statical means of predicting disruptions in supply chains, and how interruptions can derail the entire market. It was a fascinating and timely discussion, especially considering the current health crisis in China, one of our main manufacturing suppliers.  

Abstract

Global and drawn-out supply chains are being exposed to various disruptive events which have a big impact on the companies supply chain. Efficient and rapid return to normality is critical in the aftermath of an emergency event. The impacts of supply chain disruption, which includes shipment delays, increase in product cost, customer dissatisfaction and decrease in service level, can be reduced if there is a better understanding of the type of disrupting events, their probability of occurrence, and their impact on the supply chain. Simulation model can be built to estimating resilience of supply chain networks. This model can be improved if researches can incorporate the updated probability of risk for various events associated with supply chain operation. In this project, Bayesian network is used to estimate the updated risk probability, and framework is developed seamlessly connect the input from various source in to the risk probability estimation model, and finally to the simulation model to estimate resilience of the supply chain network.