Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts
Data collection from distributed automated production systems is one of the main prerequisites to leverage information gain from data analysis in the context of Industrie 4.0, e.g., for the optimization of product quality. However, the realization of data collection architectures is associated with...
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doaj-f7e3a8d817434371bd0219a93bbd5a922021-01-23T00:04:35ZengMDPI AGSensors1424-82202021-01-012174574510.3390/s21030745Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation EffortsEmanuel Trunzer0Birgit Vogel-Heuser1Jan-Kristof Chen2Moritz Kohnle3Institute of Automation and Information Systems, Technical University of Munich, 85748 Garching, GermanyInstitute of Automation and Information Systems, Technical University of Munich, 85748 Garching, GermanyInstitute of Automation and Information Systems, Technical University of Munich, 85748 Garching, GermanyInstitute of Automation and Information Systems, Technical University of Munich, 85748 Garching, GermanyData collection from distributed automated production systems is one of the main prerequisites to leverage information gain from data analysis in the context of Industrie 4.0, e.g., for the optimization of product quality. However, the realization of data collection architectures is associated with immense implementation efforts due to the heterogeneity of systems, protocols, and interfaces, as well as the multitude of involved disciplines in such projects. Therefore, this paper contributes with an approach for the model-driven generation of data collection architectures to significantly lower manual implementation efforts. Via model transformations, the corresponding source code is automatically generated from formalized models that can be created using a graphical domain-specific language. The automatically generated architecture features support for various established IIoT protocols. In a lab-scale evaluation and a unique generalized extrapolation study, the significant effort savings compared to manual programming could be quantified. In conclusion, the proposed approach can successfully mitigate the current scientific and industrial challenges to enable wide-scale access to industrial data.https://www.mdpi.com/1424-8220/21/3/745data collection architecturedata analysisdomain-specific languageIIoT architectures and frameworksIIoT communicationindustrial automation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Emanuel Trunzer Birgit Vogel-Heuser Jan-Kristof Chen Moritz Kohnle |
spellingShingle |
Emanuel Trunzer Birgit Vogel-Heuser Jan-Kristof Chen Moritz Kohnle Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts Sensors data collection architecture data analysis domain-specific language IIoT architectures and frameworks IIoT communication industrial automation |
author_facet |
Emanuel Trunzer Birgit Vogel-Heuser Jan-Kristof Chen Moritz Kohnle |
author_sort |
Emanuel Trunzer |
title |
Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts |
title_short |
Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts |
title_full |
Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts |
title_fullStr |
Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts |
title_full_unstemmed |
Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts |
title_sort |
model-driven approach for realization of data collection architectures for cyber-physical systems of systems to lower manual implementation efforts |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-01-01 |
description |
Data collection from distributed automated production systems is one of the main prerequisites to leverage information gain from data analysis in the context of Industrie 4.0, e.g., for the optimization of product quality. However, the realization of data collection architectures is associated with immense implementation efforts due to the heterogeneity of systems, protocols, and interfaces, as well as the multitude of involved disciplines in such projects. Therefore, this paper contributes with an approach for the model-driven generation of data collection architectures to significantly lower manual implementation efforts. Via model transformations, the corresponding source code is automatically generated from formalized models that can be created using a graphical domain-specific language. The automatically generated architecture features support for various established IIoT protocols. In a lab-scale evaluation and a unique generalized extrapolation study, the significant effort savings compared to manual programming could be quantified. In conclusion, the proposed approach can successfully mitigate the current scientific and industrial challenges to enable wide-scale access to industrial data. |
topic |
data collection architecture data analysis domain-specific language IIoT architectures and frameworks IIoT communication industrial automation |
url |
https://www.mdpi.com/1424-8220/21/3/745 |
work_keys_str_mv |
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