A Hybrid Knowledge Graph and Bayesian Network Approach for Analyzing Supply Chain Resilience

Abstract

Supply Chain Risk Management focuses on the identification, assessment and management of disruptive events that can affect companies, transport routes and resources involved in critical goods supply chains. Modern supply chains consist of interconnected components that can be complex and dynamic in nature. In this demo, we present our system for analysing the resilience of supply chains for crisis relevant products. A dependency Bayesian Network is automatically generated from relevant information about the supply chain maintained in a Knowledge Graph. The main objective of the proposed approach is the early identification of bottlenecks and timely prediction of the consequences of probable disruptions of the network.