Digital Twin as Enabler for an Innovative Digital Shopfloor Management System in the ESB Logistics Learning Factory at Reutlingen - University
Open accessAbstract
Technologies for mapping the “digital twin” have been under development for approximately 20 years. Nowadays increasingly intelligent, individualized products encourages companies to respond innovatively to customer requirements and to handle the rising product variations quickly. An integrated engineering network, spanning across the entire value chain, is operated to intelligently connect various company divisions, and to generate a business ecosystem for products, services and communities. The conditions for the digital twin are thereby determined in which the digital world can be fed into the real, and the real world back into the digital to deal such intelligent products with rising variations. The term digital twin can be described as a digital copy of a real factory, machine, worker etc., that is created and can be independently expanded, automatically updated as well as being globally available in real time. Every real product and production site is permanently accompanied by a digital twin. First prototypes of such digital twins already exist in the ESB Logistics Learning Factory on a cloud- and app-based software that builds on a dynamic, multidimensional data and information model. A standardized language of the robot control systems via software agents and positioning systems has to be integrated. The aspect of the continuity of the real factory in the digital factory as an economical means of ensuring continuous actuality of digital models looks as the basis of changeability. For the indoor localization sensor combinations that in addition to the hardware already contain the software required for the sensor data fusion should be used. Processing systems, scenario-live-simulations and digital shop floor management results in a mandatory procedural combination. Essential to the digital twin is the ability to consistently provide all subsystems with the latest state of all required information, methods and algorithms.
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Physical objects interact with complex environments and reflect the dynamics of the physical context in which they operate.
“Physical objects interact with very complex environments and are immersed in them.They reflect the dynamics of the physical context in which they are operating [141].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [141]
Section 2.3 describes autonomous vehicles operating amid dynamic logistics and production processes, and the Conclusion discusses interactions between people, machines, and products. But Section 3 says changes in the real world are reflected in the digital world; it does not say that physical objects themselves reflect the dynamics of a complex environment. (LLM, conf=0.77)
Experimental — accuracy not yet measuredThere are ongoing technological trends for creating Digital Twins in several fields, including Smart Cities, traffic, Aerospace, Aircraft fleet management, and Innovative Factory.
“There are ongoing technological trends for creating Digital Twins in several fields: Smart Cities [141] [202] or specific issues of the cities, like traffic [203], Aerospace [204], Aircraft fleet management [205], Innovative Factory [206] 228] are emerging.”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [141]
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- Authors
- Brenner, B., & Hummel, V.
- Affiliations
- Reutlingen University (DE)
- Corresponding author
- Brenner, Beate
- Venue
- Procedia Manufacturing
- Publisher
- Elsevier BV
- Published
- 2017
- Volume
- 9
- Pages
- 198-205
- ISSN
- 2351-9789 (ISSN-L)
- OpenAlex
- W2668510504
- Cited by
- 212
- References
- 0
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 28 · 2023: 33 · 2022: 22 · 2021: 37 · 2020: 35 · 2019: 19 · 2018: 7 · 2017: 1
- FWCI
- 18.59
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Procedia Manufacturing (publishedVersion, cc-by-nc-nd)
- Reutlingen University Academic Bibliography (Reutlingen University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, learning factory, logistics, cloud-based software, robot control system, software agents, indoor positioning, sensor fusion, scenario simulation, product variation, real-time data exchange
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