A microservices-based architecture for data and software management of heavy equipment digital twins

Victor Zhidchenko (Corresponding author), Egor Startcev, Juha Kortelainen, Akhtar Zeb, Leo Torvikoski, Saeid Torkabadi, Heikki Handroos

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

2 Citations (Scopus)

Abstract

Digital twins improve the performance of heavy equipment and decrease its operational costs. To be effective, they must run along decades of a real machine lifecycle. Ensuring coherence between a real machine and its digital twin over such a long period is a challenging task that has not yet been well-studied. This task involves preserving the design and operational data and periodic execution of digital twin software that processes such data. The circumstances of heavy equipment operation complicate the task. This paper considers the problem of digital twin data and software management in light of the unique challenges related to heavy equipment. It presents an experimental case study for running digital twins of mobile log cranes using a data model and a microservices-based architecture developed by the authors. The results demonstrate the capability of the architecture for running physics-based digital twins of heavy equipment in a heterogeneous execution environment consisting of local, edge, and cloud computing resources.

Original languageEnglish
Title of host publication2023 IEEE 21st International Conference on Industrial Informatics, INDIN 2023
EditorsHelene Dorksen, Stefano Scanzio, Jurgen Jasperneite, Lukasz Wisniewski, Kim Fung Man, Thilo Sauter, Lucia Seno, Henning Trsek, Valeriy Vyatkin
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages8
ISBN (Electronic)9781665493130
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Article in a conference publication
Event21st IEEE International Conference on Industrial Informatics, INDIN 2023 - Lemgo, Germany
Duration: 17 Jul 202320 Jul 2023

Publication series

SeriesIEEE International Conference on Industrial Informatics (INDIN)
Volume2023-July
ISSN1935-4576

Conference

Conference21st IEEE International Conference on Industrial Informatics, INDIN 2023
Country/TerritoryGermany
CityLemgo
Period17/07/2320/07/23

Keywords

  • cloud computing
  • data model
  • digital twin
  • digitalisation
  • edge computing
  • simulation

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