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Industrial Plant Topology Models to Facilitate Automation Engineering

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Systems Modelling and Management (ICSMM 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1262))

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Abstract

Industrial plant topology models can potentially automate many automation engineering tasks that are today carried out manually. Information on plant topologies is today mostly available in informal CAD drawings, but not formal models that transformations could easily process. The upcoming DEXPI/ISO15926 standard may enable turning CAD drawings into such models, but was so far mainly used for data exchange. This paper proposes extensions to the CAYENNE method for control logic and process graphics generation to utilize DEXPI models and demonstrates the supported model transformation chain prototypically in two case studies involving industrial plants. The results indicate that the model expressiveness and mappings were adequate for the addressed use cases and the model processing could be executed in the range of minutes.

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Notes

  1. 1.

    https://www.automationml.org/o.red.c/tools.html.

  2. 2.

    https://dexpi.org.

  3. 3.

    https://digitalnext-bilfinger.com/solutions/pidgraph.

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Author information

Authors and Affiliations

  1. ABB Corporate Research, Ladenburg, Germany

    Heiko Koziolek & Julius Rückert

  2. Hochschule Pforzheim, Pforzheim, Germany

    Andreas Berlet

Authors
  1. Heiko Koziolek
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  2. Julius Rückert
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  3. Andreas Berlet
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Corresponding author

Correspondence to Heiko Koziolek .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Önder Babur

  2. University of Antwerp, Antwerp, Belgium

    Joachim Denil

  3. Technical University of Munich, Munich, Germany

    Birgit Vogel-Heuser

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Koziolek, H., Rückert, J., Berlet, A. (2020). Industrial Plant Topology Models to Facilitate Automation Engineering. In: Babur, Ö., Denil, J., Vogel-Heuser, B. (eds) Systems Modelling and Management. ICSMM 2020. Communications in Computer and Information Science, vol 1262. Springer, Cham. https://doi.org/10.1007/978-3-030-58167-1_8

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  • DOI: https://doi.org/10.1007/978-3-030-58167-1_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58166-4

  • Online ISBN: 978-3-030-58167-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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