Modeling Supply Network Reliability and Resilience using Dynamic Bayesian Networks

The resilience of supply networks to catastrophic events has received increased prominence following the effects on global supply of intentional and natural hazards, such as 9/11 and the Japanese tsunami respectively. We examine how supply network resilience relates to, for example, reliability, robustness and risk, in order to consider how we might construct models to support assessment of supply network resilience. We explore the use of Dynamic Bayesian Networks to model uncertainties in events affecting supply and to examine how these uncertainties propagate through supply networks over time. Using simple examples, we examine how such a modeling approach can be used to assess the impact of different strategies intended to improve supply networks resilience