Geographic Information Science and Technology as Key Approach to unveil the Potential of Industry 4.0 - How Location and Time Can Support Smart Manufacturing

Stefan Schabus, Johannes Scholz

Abstract

Productivity of manufacturing processes in Europe is a key issue. Therefore, smart manufacturing and Industry 4.0 are terms that subsume innovative ways to digitally support manufacturing. Due to the fact, that geography is currently making the step from outdoor to indoor space, the approach presented here utilizes Geographical Information Science applied to smart manufacturing. The objective of the paper is to model an indoor space of a production environment and to apply Geographic Information Science methods. In detail, movement data and quality measurements are visualized and analysed using spatial-temporal analysis techniques to compare movement and transport behaviours. Artificial neural network algorithms can support the structured analysis of (spatial) Big Data stored in manufacturing companies. In this article, the basis for a) GIS-based visualization and b) data analysis with self-learning algorithms, are the location and time when and where manufacturing processes happen. The results show that Geographic Information Science and Technology can substantially contribute to smart manufacturing, based on two examples: data analysis with Self Organizing Maps for human visual exploration of historically recorded data and an indoor navigation ontology for the modelling of indoor production environments and autonomous routing of production assets.

References

  1. Al Nuaimi, K. and Kamel, H. (2011), A survey of indoor positioning systems and algorithms, in 'Innovations in Information Technology (IIT), 2011 International Conference on', IEEE, pp. 185-190.
  2. Ascraft. H., 2008. Building information modeling: A framework for collaboration. Construction Lawyer, 28(3):1-14, 2008.
  3. Barnes, J., Rizos, C., Wang, J., Small, D., Voigt, G. and Gambale, N. (2003), 'High precision indoor and outdoor positioning using locatanet', Journal of Global Positioning System 2(2), 73-82.
  4. Chrisman, N. R., Cowen, D. J., Fisher, P. F., Goodchild, M. F., & Mark, D. M. 1989. Geographic information systems. Geography in America, 353-375.
  5. Compieta, P., Di Martino, S., Bertolotto, M., Ferrucci, F. and Kechadi, T. 2007, 'Exploratory spatio-temporal data mining and visualization', Journal of Visual Languages & Computing 18(3), 255-279.
  6. Davis, J., Edgar, T., Porter, J., Bernaden, J., & Sarli, M. 2012. Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Computers & Chemical Engineering, 47, 145-156.
  7. De Smith, M. J., Goodchild, M. F., & Longley, P., 2007. Geospatial analysis: a comprehensive guide to principles, techniques and software tools. Troubador Publishing Ltd.
  8. Geng H, (eds), 2005, Semiconductor manufacturing handbook. McGraw-Hill.
  9. Giudice, N. A., Walton, L. A., Worboys, M. 2010, The informatics of indoor and outdoor space: A research agenda. In Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness, ACM, pages 47-53.
  10. Goetz, M., 2012, Using Crowdsourced Indoor Geodata for the Creation of a Three-Dimensional Indoor Routing Web Application. Future Internet 4(2): 575-591.
  11. Goodchild, M. F. 1991. Geographic information systems. Journal of Retailing,67(1), 3-15.
  12. Gruber. T. R., 1995, Toward Principles for the design of ontologies used for knowledge sharing? International journal of human-computer studies, 43(5):907-928.
  13. Hägerstrand, T., 1970. What about people in regional science?. Papers of the Regional Science Association 24 (1): 6-21.
  14. Janowicz, K., 2008. Observation driven geo-ontology engineering. Transactions in GIS, 16(3):351-374, Kohonen, T. (1998), 'The self-organizing map', Neurocomputing 21(1), 1-6.
  15. Kohonen T, 2013, Essentials of the self-organizing map. Neural Networks, 37:52-65.
  16. Küpper, A., 2005. Location-based services: fundamentals and operation. John Wiley & Sons.
  17. Back, S., Kranzer, S., Heistracher, T. and Lampoltshammer, T., 2014, Bridging SCADA Systems and GI Systems. In: 2014 IEEE World Forum on Internet of Things (WF-IoT) (WF-IoT 2014), Seoul, Korea, pp. 41-44.
  18. Li, B., Quader, I. J. and Dempster, A. G. 2008, 'On outdoor positioning with wi-fi', Journal of Global Positioning Systems 7(1), 18-26.
  19. Longley, P. A., Goodchild, M. F., Maguire, D. J., and Rhind, D. W., 2011. Geographic Information Systems and Science. England: John Wiley & Sons, Ltd.
  20. Mautz, R. 2008, Combination of indoor and outdoor positioning, in 781st International Conference on Machine Control & Guidance'.
  21. Meijers, M., Zlatanova, S., and Pfeifer N., 2005, 3D geoinformation indoors: structuring for evacuation. In Proceedings of Next generation 3D city models, pages: 21-22.
  22. Nyström, R. H., Harjunkoski, I. and Kroll, A. (2006), 'Production optimization for continuously operated processes with optimal operation and scheduling of multiple units', Computers & chemical engineering 30(3), 392-406.
  23. Osswald S, Weiss A and Tscheligi M, 2013, Designing wearable devices for the factory: Rapid contextual experience prototyping. In: International Conference on Collaboration Technologies and Systems (CTS) 2013, IEEE, 517-521.
  24. Peuquet, D. J., 2001. Making space for time: Issues in space-time data representation. GeoInformatica, 5(1), 11-32.
  25. Raubal, M., and Worboys, M.: A formal model of the process of wayfinding in built environments. In: Spatial information theory. Cognitive and Computational Foundations of Geographic Information Science, Lecture Notes in Computer Science 1661 (1999) 381-399.
  26. Raubal, M.: Ontology and epistemology for agent-based wayfinding simulation. International Journal of Geographical Information Science 15(7) (2001) 653- 665.
  27. Schabus, S., Scholz, J., and Skupin, A., 2014, Spatialtemporal Patterns of Production Assets in an Indoor Production Environment. In Proceedings of Workshop "Analysis of Movement Data'14" Workshop at GIScience 2014, Poster Presentation, Vienna, Austria. Web: http://blogs.utexas.edu/amd2014/
  28. Scholz, J. and Schabus, S., 2014, An indoor navigation ontology for production assets in a production environment, in 'Proceedings of GIScience 2014, Vienna, Austria - Lecture Notes in Computer Science, Springer'.
  29. Skupin, A. (2010), Tri-space: Conceptualization, transformation, visualization, in 'Sixth International Conference on Geographic Information Science', pp. 14-17.
  30. Worboys, M. 2012, Modelling Indoor Space. In: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness, ACM, pages 1 - 6.
  31. Xiang, Z., Song, S., Chen, J., Wang, H., Huang, J. and Gao, X. (2004), 'A wireless lan-based indoor positioning technology', IBM Journal of Research and Development 48(5.6), 617-626.
  32. Yu, H., 2006. Spatio-temporal GIS Design for Exploring Interactions of Human Activities. Cartography and Geographic Information Science, 33(1), 3-19.
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Paper Citation


in Harvard Style

Schabus S. and Scholz J. (2015). Geographic Information Science and Technology as Key Approach to unveil the Potential of Industry 4.0 - How Location and Time Can Support Smart Manufacturing . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-123-6, pages 463-470. DOI: 10.5220/0005510804630470


in Bibtex Style

@conference{icinco15,
author={Stefan Schabus and Johannes Scholz},
title={Geographic Information Science and Technology as Key Approach to unveil the Potential of Industry 4.0 - How Location and Time Can Support Smart Manufacturing},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2015},
pages={463-470},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005510804630470},
isbn={978-989-758-123-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Geographic Information Science and Technology as Key Approach to unveil the Potential of Industry 4.0 - How Location and Time Can Support Smart Manufacturing
SN - 978-989-758-123-6
AU - Schabus S.
AU - Scholz J.
PY - 2015
SP - 463
EP - 470
DO - 10.5220/0005510804630470