%0 Generic %1 braun2022graphbased %A Braun, Dominik %A Müller, Timo %A Sahlab, Nada %A Jazdi, Nasser %A Schloegl, Wolfgang %A Weyrich, Michael %B 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), September, 2022 %D 2022 %K 2022ias ias %T A graph-based knowledge representation and pattern mining supporting the Digital Twin creation of existing manufacturing systems %X The creation of a Digital Twin for existing manufacturing systems, so-called brownfield systems, is a challenging task due to the needed expert knowledge about the structure of brownfield systems and the effort to realize the digital models. Several approaches and methods have already been proposed that at least partially digitalize the information about a brownfield manufacturing system. A Digital Twin requires linked information from multiple sources. This paper presents a graph-based approach to merge information from heterogeneous sources. Furthermore, the approach provides a way to automatically identify templates using graph structure analysis to facilitate further work with the resulting Digital Twin and its further enhancement.

@conference{braun2022graphbased, abstract = {The creation of a Digital Twin for existing manufacturing systems, so-called brownfield systems, is a challenging task due to the needed expert knowledge about the structure of brownfield systems and the effort to realize the digital models. Several approaches and methods have already been proposed that at least partially digitalize the information about a brownfield manufacturing system. A Digital Twin requires linked information from multiple sources. This paper presents a graph-based approach to merge information from heterogeneous sources. Furthermore, the approach provides a way to automatically identify templates using graph structure analysis to facilitate further work with the resulting Digital Twin and its further enhancement.}, added-at = {2022-10-17T13:00:13.000+0200}, author = {Braun, Dominik and Müller, Timo and Sahlab, Nada and Jazdi, Nasser and Schloegl, Wolfgang and Weyrich, Michael}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/26c15d7616fdac68c8f6b5fa3f4346b55/taylansngerli}, booktitle = {2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), September, 2022 }, interhash = {a9042781ff961ac83f28697b4499045e}, intrahash = {6c15d7616fdac68c8f6b5fa3f4346b55}, keywords = {2022ias ias}, timestamp = {2022-10-17T11:00:13.000+0200}, title = {A graph-based knowledge representation and pattern mining supporting the Digital Twin creation of existing manufacturing systems }, year = 2022 }