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Publikationstyp: Konferenz: Paper
Art der Begutachtung: Peer review (Publikation)
Titel: Generative and model-driven SDK development for the industrie 4.0 digital twin
Autor/-in: Braunisch, Nico
Ristin, Marko
Lehmann, Robert
van de Venn, Hans Wernher
et. al: No
DOI: 10.1109/ETFA45728.2021.9613164
10.21256/zhaw-23646
Angaben zur Konferenz: 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021
Erscheinungsdatum: 9-Sep-2021
Verlag / Hrsg. Institution: IEEE
Sprache: Englisch
Schlagwörter: Industrie 4.0
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
Zusammenfassung: Industrie 4.0 maps the digital twin as the Asset Administration Shell. To develop this digital twin, the Asset Administration Shell meta-model is used. A developer needs highquality libraries in their programming languages to build the Asset Administration Shell in efficient and ergonomic way. The existing representations of the meta-model are inconvenient for moving from the specification to realizations in software development. This leads to many, often manual, re-implementations of the Asset Administration Shell in each programming language. We present an approach to automatically generate libraries based on the intermediate representation of the meta-model. The approach allows for practical and simple development process of Industrie 4.0 components, and scales across programming environments and future changes in the meta-model.
Weitere Angaben: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: https://digitalcollection.zhaw.ch/handle/11475/23646
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: School of Engineering
Organisationseinheit: Institut für Mechatronische Systeme (IMS)
Enthalten in den Sammlungen:Publikationen School of Engineering

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Braunisch, N., Ristin, M., Lehmann, R., & van de Venn, H. W. (2021, September 9). Generative and model-driven SDK development for the industrie 4.0 digital twin. 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021. https://doi.org/10.1109/ETFA45728.2021.9613164
Braunisch, N. et al. (2021) ‘Generative and model-driven SDK development for the industrie 4.0 digital twin’, in 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021. IEEE. Available at: https://doi.org/10.1109/ETFA45728.2021.9613164.
N. Braunisch, M. Ristin, R. Lehmann, and H. W. van de Venn, “Generative and model-driven SDK development for the industrie 4.0 digital twin,” in 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021, Sep. 2021. doi: 10.1109/ETFA45728.2021.9613164.
BRAUNISCH, Nico, Marko RISTIN, Robert LEHMANN und Hans Wernher VAN DE VENN, 2021. Generative and model-driven SDK development for the industrie 4.0 digital twin. In: 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021. Conference paper. IEEE. 9 September 2021
Braunisch, Nico, Marko Ristin, Robert Lehmann, and Hans Wernher van de Venn. 2021. “Generative and Model-Driven SDK Development for the Industrie 4.0 Digital Twin.” Conference paper. In 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021. IEEE. https://doi.org/10.1109/ETFA45728.2021.9613164.
Braunisch, Nico, et al. “Generative and Model-Driven SDK Development for the Industrie 4.0 Digital Twin.” 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 7-10 September 2021, IEEE, 2021, https://doi.org/10.1109/ETFA45728.2021.9613164.


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