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Authors: Tonja Heinemann ; Marwin Gihr ; Oliver Riedel and Armin Lechler

Affiliation: University of Stuttgart, Institute for Control Engineering of Machine Tools and Manufacturing Units, Seidenstraße 36, Stuttgart, Germany

Keyword(s): OPC UA, Information Model, Standardization.

Abstract: This work analyzes the Open Platform Communications Unified Architecture (OPC UA) specifications for flat glass, plastics and rubber, machine vision, ISA-95 and machine tools regarding their job descriptions. Common contents of job models in the domain of machinery are deducted. Using a structured qualitative content analysis, more than 70 functional elements used in OPC UA job models have been identified. While some of these functional elements are modeled similarly in multiple domains, major differences are identified for other functional elements. Especially those differences constitute impediments in the standardization of industrial communication. The results of this work harmonize the contents and the modeling techniques regarding machining jobs in OPC UA and provide a generally applicable method for the standardization of machine communication throughout different domains. With this method for standardization, this work contributes directly to the goal of OPC UA, to easily exc hange data between platforms from multiple vendors. (More)

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Paper citation in several formats:
Heinemann, T.; Gihr, M.; Riedel, O. and Lechler, A. (2022). Towards Data-driven Production: Analysis of Data Models Describing Machinery Jobs in OPC UA. In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO; ISBN 978-989-758-585-2; ISSN 2184-2809, SciTePress, pages 729-736. DOI: 10.5220/0011142900003271

@conference{icinco22,
author={Tonja Heinemann. and Marwin Gihr. and Oliver Riedel. and Armin Lechler.},
title={Towards Data-driven Production: Analysis of Data Models Describing Machinery Jobs in OPC UA},
booktitle={Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO},
year={2022},
pages={729-736},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011142900003271},
isbn={978-989-758-585-2},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - ICINCO
TI - Towards Data-driven Production: Analysis of Data Models Describing Machinery Jobs in OPC UA
SN - 978-989-758-585-2
IS - 2184-2809
AU - Heinemann, T.
AU - Gihr, M.
AU - Riedel, O.
AU - Lechler, A.
PY - 2022
SP - 729
EP - 736
DO - 10.5220/0011142900003271
PB - SciTePress