%0 Conference Paper %1 10.1007/978-3-030-85874-2_35 %A Michael, Judith %A Wortmann, Andreas %B Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems %C Cham %D 2021 %E Dolgui, Alexandre %E Bernard, Alain %E Lemoine, David %E von Cieminski, Gregor %E Romero, David %I Springer International Publishing %K rwthaachense %P 333--341 %T Towards Development Platforms for Digital Twins: A Model-Driven Low-Code Approach %U https://link.springer.com/chapter/10.1007/978-3-030-85874-2_35 %X Digital Twins in smart manufacturing must be highly adaptable for different challenges, environments, and system states. In practice, there is a need for enabling the configuration of Digital Twins by domain experts. Low-code approaches seem to be a meaningful solution for configuration purposes but often lack extension options. We propose a model-driven low-code approach for the configuration and reconfiguration of Digital Twins using language plugins. This approach uses model-driven software engineering and software language engineering methods to derive a configurable digital twin implementation. Moreover, we discuss some remaining challenges such as interoperability, language modularity, evolution, integration of assistive services, collaborative development, and web-based debugging. %@ 978-3-030-85874-2

@inproceedings{10.1007/978-3-030-85874-2_35, abstract = {Digital Twins in smart manufacturing must be highly adaptable for different challenges, environments, and system states. In practice, there is a need for enabling the configuration of Digital Twins by domain experts. Low-code approaches seem to be a meaningful solution for configuration purposes but often lack extension options. We propose a model-driven low-code approach for the configuration and reconfiguration of Digital Twins using language plugins. This approach uses model-driven software engineering and software language engineering methods to derive a configurable digital twin implementation. Moreover, we discuss some remaining challenges such as interoperability, language modularity, evolution, integration of assistive services, collaborative development, and web-based debugging.}, added-at = {2021-12-07T13:13:13.000+0100}, address = {Cham}, author = {Michael, Judith and Wortmann, Andreas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/27fd49de64dd76907061c897e1fba2dad/isw-bibliothek}, booktitle = {Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems}, editor = {Dolgui, Alexandre and Bernard, Alain and Lemoine, David and von Cieminski, Gregor and Romero, David}, interhash = {fe8d101516efbfb2b0a779bd96a34c5b}, intrahash = {7fd49de64dd76907061c897e1fba2dad}, isbn = {978-3-030-85874-2}, keywords = {rwthaachense}, pages = {333--341}, publisher = {Springer International Publishing}, timestamp = {2021-12-13T08:56:16.000+0100}, title = {Towards Development Platforms for Digital Twins: A Model-Driven Low-Code Approach}, url = {https://link.springer.com/chapter/10.1007/978-3-030-85874-2_35}, year = 2021 }