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  4. A Hybrid Knowledge Graph and Bayesian Network Approach for Analyzing Supply Chain Resilience
 
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June 2023
Conference Paper
Title

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.
Author(s)
Karam, Naouel  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Matini, Shirkouh
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Laas, Roman
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Hoppe, Thomas  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Mainwork
The Semantic Web: ESWC 2023 Satellite Events. Proceedings  
Conference
Extended Semantic Web Conference 2023  
DOI
10.1007/978-3-031-43458-7_5
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • Automatic bottleneck identification

  • Bayesian Network

  • Crisis management

  • Knowledge Graph

  • Supply chain resilience

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