Long living human-machine systems in construction and production enabled by digital twins-Reference-Cited by-同舟云学术

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

Published:2024-09-01 Issue:9 Volume:72 Page:789-814
ISSN:0178-2312
Container-title:at - Automatisierungstechnik
language:en
Short-container-title:

Author:

Vogel-Heuser Birgit¹,Hartl Fandi¹,Wittemer Moritz²,Zhao Jingyun¹,Mayr Andreas³,Fleischer Martin⁴,Prinz Theresa⁴,Fischer Anne⁵,Trauer Jakob⁶,Schroeder Philipp⁶,Goldbach Ann-Kathrin⁷,Rothmeyer Florian⁵,Zimmermann Markus⁶,Bletzinger Kai-Uwe⁷,Fottner Johannes⁵,Daub Rüdiger³,Bengler Klaus⁴,Borrmann André⁸,Zaeh Michael F.³,Wudy Katrin²

Affiliation:

1. Technical University of Munich, Institute of Automation and Information Systems , Boltzmannstr. 15, 85748 Garching bei München , Germany

2. Technical University of Munich, Professorship of Laser-based Additive Manufacturing , Boltzmannstr. 15, 85748 Garching bei München , Germany

3. Technical University of Munich, Institute for Machine Tools and Industrial Management , Boltzmannstr. 15, 85748 Garching bei München , Germany

4. Chair of Ergonomics , Technical University of Munich , Boltzmannstr. 15, 85748 Garching bei München , Germany

5. Chair of Materials Handling, Material Flow, Logistics , Technical University of Munich , Boltzmannstr. 15, 85748 Garching bei München , Germany

6. Laboratory for Product Development and Lightweight Design , Technical University of Munich , Boltzmannstr. 15, 85748 Garching bei München , Germany

7. Chair of Structural Analysis , Technical University of Munich , Arcisstr. 21, 80333 Munich , Germany

8. Chair of Computational Modeling and Simulation , Technical University of Munich , Arcisstr. 21, 80333 Munich , Germany

Abstract

Abstract 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.

Publisher

Walter de Gruyter GmbH

Link

https://www.degruyter.com/document/doi/10.1515/auto-2023-0227/pdf

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