Graphical modeling notation for data collection and analysis architectures in cyber-physical systems of systems

Industrie 4.0 and data analytics blur the separation of operational and information technology that prevailed for industrial automation over the last decades. Decentralized control systems for production plants and robot cells collaborate actively with higher-level systems for big data analytics. In...

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Veröffentlicht in:Journal of industrial information integration Jg. 19; S. 100155
Hauptverfasser: Trunzer, Emanuel, Wullenweber, Anne, Vogel-Heuser, Birgit
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.09.2020
Schlagworte:
Big data in robotics and automation
Cyber-physical systems of systems
Data collection
Factory automation
Graphical modeling notation
Systems modeling
Systems modeling
Data collection
Graphical modeling notation
Big data in robotics and automation
Cyber-physical systems of systems
Factory automation
ISSN:2452-414X, 2452-414X
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Zusammenfassung:Industrie 4.0 and data analytics blur the separation of operational and information technology that prevailed for industrial automation over the last decades. Decentralized control systems for production plants and robot cells collaborate actively with higher-level systems for big data analytics. In parallel, the complexity of designing and operating a system architecture for data collection and analysis increases dramatically as more experts from different domains get involved. Graphical modeling notations facilitate the design process by formalizing implicit knowledge, but currently do not exist for the combined description of field layer and data analytics. Modeling the system architecture, relevant constraints, and requirements early during the design process can increase the efficiency of the system development and deployment, especially as experts with various backgrounds are involved. In this contribution, a new graphical notation is introduced and evaluated in three industrial case-studies. The notation describes the underlying hardware and software components of cyber-physical systems of systems, the flow of data, and relevant constraints. The evaluation proved that the notation is powerful in supporting the engineering of data collection and analysis architectures in industrial automation. Future work is related to extending the scope of the modeling approach to include safety applications and real-time considerations on the field level.
ISSN:2452-414X
2452-414X
DOI:10.1016/j.jii.2020.100155