Complex Network Modelling and Knowledge Graphs for Digital Twins and Industry 4.0

EasyChair Preprint 14913

Abstract

This study plans to verify the benefits of integrating Knowledge Graphs with Intelligent Digital Twins for the management of complex man-made systems through simulation. Complex systems contain large numbers of interacting parts which are difficult to fully understand and control. Examples of complex natural systems include the human body, an ecosystem, or the atmosphere. Examples of complex man-made systems include critical infrastructure such as rail, electricity, telecommunications, and water networks. Digital Twins and Digital Twins augmented with Knowledge Graphs have been proposed as tools to assist the operators of complex systems to better manage the operations of these systems under both normal and upset conditions. This study seeks to verify the benefit of Digital Twins and Digital Twins augmented with Knowledge Graphs (Intelligent Digital Twins, iDT) using simulation and the Design Science Research (DSR) methodology. The DSR methodology is well suited to this area of study as it is a problem-solving methodology that seeks to enhance human knowledge through the creation of useful artifacts.

Keyphrases: Design Science Research, Digital Twin, Industry 4.0, Knowledge Graphs, complex network systems, graph augmented digital twins, intelligent digital twins

@booklet{EasyChair:14913,
  author    = {Patrick Berry and Madhushi Bandara},
  title     = {Complex Network Modelling and Knowledge Graphs for Digital Twins and Industry 4.0},
  howpublished = {EasyChair Preprint 14913},
  year      = {EasyChair, 2024}}