Software infrastructure for ready-to-use, data analytics-based Digital Twins utilising the Asset Administration Shell

  • The advance of the Industrial Internet of Things has largely increased the availability of shop floor data for software applications in production management. Digital Twins utilise shop floor data to provide synchronised virtual representations of production resources, e.g. by applying Data analytics such as Machine Learning techniques. A main barrier to take advantage of the potential of Digital Twins is the personnel effort and skills required for development, which can be lowered by ready-to-use approaches. This article proposes a corresponding software infrastructure. Prebuilt and configurable Digital Twin components are allocated to suitable platforms and linked by suitable data connections. To enable interoperability with production management applications, the standard of the Asset Administration Shell is utilised. Establishing resource-specific shop floor data connection and transformation is facilitated by a shopfloor integration platform, which provides configurableThe advance of the Industrial Internet of Things has largely increased the availability of shop floor data for software applications in production management. Digital Twins utilise shop floor data to provide synchronised virtual representations of production resources, e.g. by applying Data analytics such as Machine Learning techniques. A main barrier to take advantage of the potential of Digital Twins is the personnel effort and skills required for development, which can be lowered by ready-to-use approaches. This article proposes a corresponding software infrastructure. Prebuilt and configurable Digital Twin components are allocated to suitable platforms and linked by suitable data connections. To enable interoperability with production management applications, the standard of the Asset Administration Shell is utilised. Establishing resource-specific shop floor data connection and transformation is facilitated by a shopfloor integration platform, which provides configurable components. The software infrastructure is demonstrated in a laboratory environment, where Digital Twins of a manufacturing machine and an assembly robot entail Machine Learning models to predict and provide capacity parameters to a discrete event simulation.show moreshow less

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Metadaten
Author:Mario Luber, Lukas Wittmann, Johannes SchilpGND
URN:urn:nbn:de:bvb:384-opus4-1293749
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/129374
ISSN:1877-0509OPAC
Parent Title (English):Procedia Computer Science
Publisher:Elsevier BV
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2026
Publishing Institution:Universität Augsburg
Release Date:2026/03/27
Volume:277
First Page:3113
Last Page:3122
DOI:https://doi.org/10.1016/j.procs.2026.02.347
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Ingenieurinformatik mit Schwerpunkt Produktionsinformatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung