Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins

• URL: http://arxiv.org/abs/2104.01854v1
• Date: Mon, 5 Apr 2021 11:07:05 GMT
• Title: Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins
• Authors: Seppo Sierla (1), Mohammad Azangoo (1), Alexander Fay (2), Valeriy Vyatkin (1 and 3), and Nikolaos Papakonstantinou (4) ((1) Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland, (2) Department of Automation Engineering, Helmut Schmidt University, Hamburg, Germany, (3) Department of Computer Science, Electrical and Space Engineering, Lule{\aa} University of Technology, Lule{\aa}, Sweden, (4) VTT Technical Research Centre of Finland Ltd, Espoo, Finland)
• Abstract summary: Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of piping and instrumentation diagrams as well as 3D pipe routing. It is necessary to develop algorithms for identifying corresponding elements such as tanks and pumps from piping and instrumentation diagrams and 3D CAD models. This article focuses on automatic generation of the graphs as a prerequisite to graph matching.
• Score: 35.37983668316551
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of Piping and Instrumentation diagrams as well as 3D pipe routing. However, a complete digital plant model requires combining these two representations. 3D pipe routing information is essential for building any accurate first-principles process simulation model. Piping and instrumentation diagrams are the primary source for control loops. In order to automatically integrate these information sources to a unified digital plant model, it is necessary to develop algorithms for identifying corresponding elements such as tanks and pumps from piping and instrumentation diagrams and 3D CAD models. One approach is to raise these two information sources to a common level of abstraction and to match them at this level of abstraction. Graph matching is a potential technique for this purpose. This article focuses on automatic generation of the graphs as a prerequisite to graph matching. Algorithms for this purpose are proposed and validated with a case study. The paper concludes with a discussion of further research needed to reprocess the generated graphs in order to enable effective matching.

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