An Architecture for Visualization of Industrial Automation Data

Guillaume Prévost, Jan Olaf Blech, Keith Foster, Heinrich W. Schmidt

2017

Abstract

We introduce a framework for visualization of data originating from industrial automation devices. Our framework uses cloud-based services to collect data from industrial automation controllers. Clients can subscribe to the data sources and visualize them in accordance with customer needs. Data from industrial automation facilities is associated with formal semantic models, such as a mathematical representation of the material flow in a production plant. The formal models are used to represent interdependencies between entities, their functionality and other descriptive elements. Ultimately this is used in the visualization and for reasoning about systems. In addition to the software framework we describe work on our demonstrator: an example factory with Raspberry Pi-based controllers that are interconnected via standard ethernet technology.

References

  1. P. Balbiani, J.-F. Condotta, and L. F. del Cerro. A new tractable subclass of the rectangle algebra. In Proceedings of the 16th International Joint Conference on Artifical Intelligence - Volume 1, pages 442447, 1999.
  2. B. Bennett, A. G. Cohn, F. Wolter, M. Zakharyaschev. Multi-Dimensional Modal Logic as a Framework for Spatio-Temporal Reasoning. Applied Intelligence, Volume 17, Issue 3, Kluwer Academic Publishers, November 2002.
  3. J. O. Blech, L. Fernando, K. Foster, Abhilash G and Sudarsan Sd. Spatio-temporal Reasoning and Decision Support for Smart Energy Systems. Emerging Technologies and Factory Automation (ETFA), IEEE, 2016.
  4. J. O. Blech, I. Peake, H. Schmidt, M. Kande, A. Rahman, S. Ramaswamy, Sudarsan SD, V. Narayanan. Efficient Incident Handling in Indus- trial Automation through Collaborative Engineering. Emerging Technologies and Factory Automation (ETFA), IEEE, 2015.
  5. J. O. Blech, H. Schmidt. BeSpaceD: Towards a Tool Framework and Methodology for the Specification and Verification of Spatial Behavior of Distributed Software Component Systems, http://arxiv.org/abs/1404.3537. arXiv.org, 2014.
  6. L. Caires and L. Cardelli.A Spatial Logic for Concurrency (Part I). Information and Computation, Vol 186/2 November 2003.
  7. L. Caires and L. Cardelli. A Spatial Logic for Concurrency (Part II). Theoretical Computer Science, 322(3) pp. 517-565, September 2004.
  8. DS DELMIA V6R2013x - Fact Sheet: 3DEXPERIENCES of Global Production Systems for all stakeholders in the extended supply chain. Dassault Systèmes 2013.
  9. ENOVIA V6R2013x - Fact Sheet. Dassault Systèmes 2013 S. Hordvik, K. Oseth, J. O. Blech, P. Herrmann. A Methodology for Model-based Development and Safety Analysis of Transport Systems.Evaluation of Novel Approaches to Software Engineering, 2016.
  10. H. Kagermann, W. Wahlster, J. Helbig (eds.). Recommendations for implementing the strategic initiative INDUSTRIE 4.0 - Final report of the Industrie 4.0 Working Group. Acatech, 2013.
  11. H. K. Lin and Jenny A. Harding. A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration. Computers in Industry 58, no. 5 (2007): 428-437.
  12. M. Loskyll, J. Schlick, S. Hodek, L. Ollinger, T. Gerber, & B. Pirvu. Semantic service discovery and orchestration for manufacturing processes., 16th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 2011.
  13. S. Skiadopoulos and M. Koubarakis. On the consistency of cardinal direction constraints. Artificial Intelligence, 163(1):91135, 2005.
  14. N. Van de Weghe, B. Kuijpers, P. Bogaert, and P. De Maeyer. A qualitative trajectory calculus and the composition of its relations. In Proceedings of the 1st International Conference on GeoSpatial Semantics, pages 6076. Springer, 2005.
  15. M. Wenger, A. Zoitl, J. O. Blech, I. Peake. Remote Monitoring Infrastructure for IEC 61499 Based Control Software. 8th International Congress on Ultra Modern Telecommunications and Control Systems, IEEE, 2016.
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Paper Citation


in Harvard Style

Prévost G., Blech J., Foster K. and Schmidt H. (2017). An Architecture for Visualization of Industrial Automation Data . In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-250-9, pages 38-46. DOI: 10.5220/0006289700380046


in Bibtex Style

@conference{enase17,
author={Guillaume Prévost and Jan Olaf Blech and Keith Foster and Heinrich W. Schmidt},
title={An Architecture for Visualization of Industrial Automation Data},
booktitle={Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2017},
pages={38-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006289700380046},
isbn={978-989-758-250-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - An Architecture for Visualization of Industrial Automation Data
SN - 978-989-758-250-9
AU - Prévost G.
AU - Blech J.
AU - Foster K.
AU - Schmidt H.
PY - 2017
SP - 38
EP - 46
DO - 10.5220/0006289700380046