Advertisement

Software & Systems Modeling

, Volume 15, Issue 1, pp 17–29 | Cite as

Industry 4.0 as a Cyber-Physical System study

  • Pieter J. Mosterman
  • Justyna ZanderEmail author
Industry Voice

Abstract

Advances in computation and communication are taking shape in the form of the Internet of Things, Machine-to-Machine technology, Industry 4.0, and Cyber-Physical Systems (CPS). The impact on engineering such systems is a new technical systems paradigm based on ensembles of collaborating embedded software systems. To successfully facilitate this paradigm, multiple needs can be identified along three axes: (i) online configuring an ensemble of systems, (ii) achieving a concerted function of collaborating systems, and (iii) providing the enabling infrastructure. This work focuses on the collaborative function dimension and presents a set of concrete examples of CPS challenges. The examples are illustrated based on a pick and place machine that solves a distributed version of the Towers of Hanoi puzzle. The system includes a physical environment, a wireless network, concurrent computing resources, and computational functionality such as, service arbitration, various forms of control, and processing of streaming video. The pick and place machine is of medium-size complexity. It is representative of issues occurring in industrial systems that are coming online. The entire study is provided at a computational model level, with the intent to contribute to the model-based research agenda in terms of design methods and implementation technologies necessary to make the next generation systems a reality.

Keywords

Cyber-Physical Systems Industry 4.0 Modeling and simulation Industrial practice 

References

  1. 1.
    acatech Final report of the Industrie 4.0 Working Group. Securing the future of German manufacturing industry recommendations for implementing the strategic initiative industrie 4.0. acatech—National Academy of Science and Engineering, Munich, Apr 2013Google Scholar
  2. 2.
    acatech Position Paper. Cyber-physical systems. Driving force for innovation in mobility, health, energy and production. acatech—National Academy of Science and Engineering, Munich, Dec 2011Google Scholar
  3. 3.
    Arrieta, A., Sagardui, G., Etxeberria, L.: A model-based testing methodology for the systematic validation of highly configurable cyber-physical systems. In: The Sixth International Conference on Advances in System Testing and Validation Lifecycle, pp. 66–72 (2014)Google Scholar
  4. 4.
    Bringmann, E., Krämer, A.: Model-based testing of automotive systems. In: Proceedings of the 2008 International Conference on Software Testing, Verification, and Validation, ICST ’08, pp. 485–493. IEEE Computer Society, Washington (2008)Google Scholar
  5. 5.
    Di Natale, M., Guo, L., Zeng, H., Sangiovanni-Vincentelli, A.: Synthesis of multitask implementations of Simulink models with minimum delays. IEEE Trans. Ind. Inf. 6(4), 637–651 (2010)CrossRefGoogle Scholar
  6. 6.
    France, R.B., Rumpe, B.: The evolution of modeling research challenges. Softw. Syst. Model. 12(2), 223–225 (2013)CrossRefGoogle Scholar
  7. 7.
    Gyrard, A., Bonnet, C., Boudaoud, K.: Enrich machine-to-machine data with semantic web technologies for cross-domain applications. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 559–564, March 2014Google Scholar
  8. 8.
    Huhn, M., Mutz, M., Diethers, K., Florentz, B., Daginnus, M.: Applications of static analysis on UML models in the automotive domain. In: Schnieder, E., Tarnai, G. (eds.) Formal Methods for Automation and Safety in Railway and Automotive Systems (FORMS/FORMAT 2004), pp. 161–172, Braunschweig, Dec 2004Google Scholar
  9. 9.
    Kaiser, B., Klaas, V., Schulz, S., Herbst, C., Lascych, P.: Integrating system modelling with safety activities. In: Computer Safety, Reliability, and Security, 29th International Conference, SAFECOMP 2010, Vienna, 14–17 Sept 2010. Proceedings, pp. 452–465 (2010)Google Scholar
  10. 10.
    Lee, E.A.: Cyber physical systems: design challenges. In: International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC), May 2008. Invited paperGoogle Scholar
  11. 11.
    Levinson, J., Thrun, S.: Automatic online calibration of cameras and lasers. In: Proceedings of Robotics: Science and Systems, Berlin, June 2013Google Scholar
  12. 12.
    Liu, J., Zhao, F.: Towards service-oriented networked embedded computing. Technical report MSR-TR-2005-28, Microsoft Research, Feb 2005Google Scholar
  13. 13.
    MathWorks\(^{\textregistered }\) product families, Sept 2012Google Scholar
  14. 14.
    Mosterman, P.J., Sanabria, D.E., Bilgin, E., Zhang, K., Zander, J.: A heterogeneous fleet of vehicles for automated humanitarian missions. Comput. Sci. Eng. 12, 90–95 (2014)CrossRefGoogle Scholar
  15. 15.
    Mosterman, P.J., Sztipanovits, J., Engell, S.: Computer automated multi-paradigm modeling in control systems technology. IEEE Trans. Control Syst. Technol. 12(2), 223–234 (2004)CrossRefGoogle Scholar
  16. 16.
    Mosterman, P.J., Vangheluwe, H.: Computer automated multi-paradigm modeling in control system design. In: Proceedings of the IEEE International Symposium on Computer-Aided Control System Design, pp. 65–70, Anchorage, Alaska, Sept 2000Google Scholar
  17. 17.
    Mosterman, P.J., Zander, J.: Cyber-physical systems challenges—a needs analysis for collaborating embedded software systems. Softw. Syst. Model. (2015). doi: 10.1007/s10270-015-0469-x
  18. 18.
    Mosterman, P.J., Zander, J.: GitHub Repository: Towers of Hanoi in MATLAB/Simulink for Industry 4.0. doi: 10.5281/zenodo.13977
  19. 19.
    Mosterman, P.J., Zander, J., Han, Z.: The Towers of Hanoi as a cyber-physical system education case study. In: Proceedings of the First Workshop on CPS Education, Philadelphia, PA, April 2013Google Scholar
  20. 20.
    National Institute of Standards and Steering Committee Technology: Strategic vision and business drivers for 21st century cyber physical systems. Report of the Steering Committee for Foundations in Innovation for Cyber-physical Systems, Jan 2013Google Scholar
  21. 21.
    Russell, S., Dewey, D., Tegmark, M.: Research priorities for robust and beneficial artificial intelligence: an open letter, Jan 2015Google Scholar
  22. 22.
    Samad, T., Annaswamy, A. (eds.): The Impact of Control Technology. IEEE Control Systems Society, New York (2011)Google Scholar
  23. 23.
    Sanders, J.W., Smith, G.: Emergence and refinement. Form. Asp. Comput. 24(1), 45–65 (2012)CrossRefMathSciNetzbMATHGoogle Scholar
  24. 24.
    SERS Consortium: Smart emergency response system: GitHub Software Repository. doi: 10.5281/zenodo.13978
  25. 25.
    Steering Committee for Foundations in Innovation for Cyber-Physical Systems. Foundations for Innovation: Strategic opportunities for the 21\(^{{\rm st}}\) century cyber-physical systems—connecting computer and information systems with the physical world. Technical report, National Institute of Standards and Technology (NIST), March 2013Google Scholar
  26. 26.
    Uhrmacher, A.M., Weyns, D.: Multi-Agent Systems: Simulation and Applications, 1st edn. CRC Press, Boca Raton (2009)Google Scholar
  27. 27.
    Vermessan, O., Friess, P.: Internet of Things: From Research and Innovation to Market Deployment. River Publishers Series in Communication. River Publishers, Aalborg (2014)Google Scholar
  28. 28.
    Waibel, M., Beetz, M., D’Andrea, R., Janssen, R., Tenorth, M., Civera, J., Elfring, J., Gálvez-López, D., Kai Häussermann, J.M.M., Montiel, A.P., Schießle, B., Zweigle, O., van de Molengraft, R.: RoboEarth—a world wide web for robots. Robot. Autom. Mag. 18(2), 69–82 (2011)CrossRefGoogle Scholar
  29. 29.
    Zander, J.: Model in the loop test for embedded systems: (MiLEST) blockset repository. doi: 10.5281/zenodo.13983
  30. 30.
    Zander, J., Mosterman, P.J.: Computation for Humanity: Information Technology to Advance Society. CRC Press, Boca Raton (2013)Google Scholar
  31. 31.
    Zander, J., Schieferdecker, I., Mosterman, P.J.: Model-Based Testing for Embedded Systems, 1st edn. CRC Press, Boca Raton (2011)Google Scholar
  32. 32.
    Zander-Nowicka, J., Schieferdecker, I., Marrero Perez, A.: Automotive validation functions for on-line test evaluation of hybrid real-time systems. In: Autotestcon, 2006 IEEE, pp. 799–805, Sept 2006Google Scholar
  33. 33.
    Zergainoh, N.-E., Popovici, K., Jerraya, A.A., Urard, P.: Matlab based environment for designing DSP systems using IP blocks. In: Proceedings of the Workshop on Synthesis and System Integration of Mixed Information technologies, pp. 296–302, Kanazawa, Oct 2004Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.MathWorksNatickUSA
  2. 2.Worcester Polytechnic InstituteWorcesterUSA
  3. 3.School of Computer ScienceMcGill UniversityQuébec CanadaCanada

Personalised recommendations