Architecture of a Versatile Digital Twin with Socket-Based Communication and Azure DT

Josua Höfgen, Birgit Vogel-Heuser, Fandi Bi, Jingyun Zhao, André Kraft, Bernd Vojanec, Timo Markert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The concept of Digital Twin (DT) has gained widespread attention due to the rapid advancement of Industry 4.0, technologies such as IoT, big data analytics, and artificial intelligence. DT is a virtual replica of a physical object or system that enables real-time monitoring, analysis, and optimization of its performance. This work proposes a DT system, based on automated DT creation and flexible communication across platforms to realize tool independence and to allow interchangeability of the included web-deployment and simulation environments. We apply the approach to the gearbox assembly process in an industrial use case, using the Asset Administration Shell (AAS) as a common digital asset definition both for a simulation environment and a robot control program. The proposed approach addresses the challenges in representing real plants and enterprise processes in a DT by managing heterogeneous data sources, data types, data inconsistencies, and ensuring real-time capability for safety-critical applications.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PublisherIEEE Computer Society
ISBN (Electronic)9798350320695
DOIs
StatePublished - 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2023-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand
CityAuckland
Period26/08/2330/08/23

Keywords

  • Asset Administration Shell AAS
  • Azure DT
  • Digital Twin
  • Industry 4.0
  • Internet of things
  • automated creation and deployment
  • big data analytics
  • robot control program
  • simulation environment

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