Long living human-machine systems in construction and production enabled by digital twins

In the industrial sector, products evolve significantly over their operational life. A key challenge has been maintaining precise, relevant engineering data. This paper explores the digital twin concept, merging engineering and operational data to enhance product information updates. It examines dig...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Automatisierungstechnik : AT 2024-09, Vol.72 (9), p.789-814
Hauptverfasser: Vogel-Heuser, Birgit, Hartl, Fandi, Wittemer, Moritz, Zhao, Jingyun, Mayr, Andreas, Fleischer, Martin, Prinz, Theresa, Fischer, Anne, Trauer, Jakob, Schroeder, Philipp, Goldbach, Ann-Kathrin, Rothmeyer, Florian, Zimmermann, Markus, Bletzinger, Kai-Uwe, Fottner, Johannes, Daub, Rüdiger, Bengler, Klaus, Borrmann, André, Zaeh, Michael F., Wudy, Katrin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In the industrial sector, products evolve significantly over their operational life. A key challenge has been maintaining precise, relevant engineering data. This paper explores the digital twin concept, merging engineering and operational data to enhance product information updates. It examines digital twin applications in construction, material flow, manufacturing and production, citing battery production and additive manufacturing. Digital twins aid in analyzing, experimenting with, and refining a system’s design and its operation, offering insights across product and system lifecycles. This includes tackling data management and model-data consistency challenges, as well as the recognition of synergies. This paper emphasizes sustainable, efficient management of engineering information, reflecting shifts in product longevity and documentation in industrial products and machinery.
ISSN:0178-2312
2196-677X
DOI:10.1515/auto-2023-0227