Model-Based System Reconfiguration: A Descriptive Study of Current Industrial Challenges

  • Lara QasimEmail author
  • Marija Jankovic
  • Sorin Olaru
  • Jean-Luc Garnier
Conference paper


System Reconfiguration is essential in management of complex systems because it allows companies better flexibility and adaptability. System evolutions have to be managed in order to ensure system effectivity and efficiency through its whole lifecycle, in particular when it comes to complex systems that have decades of development and up to hundreds of years of usage. System Reconfiguration can be considered and deployed in different lifecycle phases. Two significant phases are considered for configuration management and System Reconfiguration: design-time – allowing system performances by modifying the architecture in early stages – and run-time – allowing optimization of performances during the in-service operations. This paper gives an overview of a field research currently ongoing to capture the strengths and the shortages in the current industrial landscape. It also discusses possible future management strategies with regard to identified issues and challenges.


  1. 1.
    ISO/IEC/IEEE/15288: Systems and software engineering–system life cycle processes (2015)Google Scholar
  2. 2.
    INCOSE: Systems engineering handbook: a guide for system life cycle processes and activities. In: Walden, D.D., Roedler, G.J., Forsberg, K., Hamelin, R.D., Shortell, T.M., (eds.) International Council on Systems Engineering, 4th edn. Wiley, San Diego (2015)Google Scholar
  3. 3.
    NASA: NASA Systems Engineering Handbook, vol. 6105 (2007)Google Scholar
  4. 4.
    Zhang, Y., Jiang, J.: Bibliographical review on reconfigurable fault-tolerant control systems. Annu. Rev. Control 32(2), 229–252 (2008)CrossRefGoogle Scholar
  5. 5.
    Stoican, F., Olaru, S.: Set-Theoretic Fault Detection and Control Design for Multisensor Systems (2013)Google Scholar
  6. 6.
    Eterno, J., Weiss, J., Looze, D., Willsky, A.: Design issues for fault tolerant-restructurable aircraft control. In: 24th IEEE Conference on Decision and Control, pp. 900–905 (1985)Google Scholar
  7. 7.
    Isermann, R.: Supervision, fault-detection and fault-diagnosis methods–an introduction. Control Eng. Pract. 5(5), 639–652 (1997)CrossRefGoogle Scholar
  8. 8.
    Reiter, R.: A theory of diagnosis from first principles. Artif. Intell. 32(1), 57–95 (1987)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Kuntz, F., Gaudan, S., Sannino, C., Laurent, É., Griffault, A., Point, G.: Model-based diagnosis for avionics systems using minimal cuts. In: Sachenbacher, M., Dressler, O., Hofbaur, M., (eds.) DX 2011, Oct 2011, pp. 138–145. Murnau, Germany (2011)Google Scholar
  10. 10.
    Ng, H.T.: Model-based, multiple fault diagnosis of time-varying, continuous physical devices. In: Proceedings 6th Conference on A. I. Applications, pp. 9–15 (1990)Google Scholar
  11. 11.
    Crow, J., Rushby, J.: Model-based reconfiguration: toward an integration with diagnosis. In: Proceedings of AAAI 1991, pp. 836–841 (1991)Google Scholar
  12. 12.
    Provan, G., Chen, Y.-L.: Model-based diagnosis and control reconfiguration for discrete event systems: an integrated approach. In: Proceedings of the 38th IEEE Conference on Decision and Control, vol. 2, pp. 1762–1768 (1999)Google Scholar
  13. 13.
    Russell, K.J., Broadwater, R.P.: Model-based automated reconfiguration for fault isolation and restoration. In: IEEE PES Innovative Smart Grid Technologies (ISGT), pp. 1–4 (2012)Google Scholar
  14. 14.
    Cui, Y., Shi, J., Wang, Z.: Backward reconfiguration management for modular avionic reconfigurable systems. IEEE Syst. J. 12(1), 137–148 (2018)CrossRefGoogle Scholar
  15. 15.
    Shan, S., Hou, Z.: Neural network NARMAX model based unmanned aircraft control surface reconfiguration. In: 9th International Symposium on Computational Intelligence and Design (ISCID), vol. 2, pp. 154–157 (2016)Google Scholar
  16. 16.
    Ludwig, M., Farcet, N.: Evaluating enterprise architectures through executable models. In: Proceedings of the 15th International Command and Control Research and Technology Symposium (2010)Google Scholar
  17. 17.
    Boardman, J., Sauser, B.: System of systems–the meaning of of. In: 2006 IEEE/SMC International Conference on System of Systems Engineering, pp. 118–123 (2006)Google Scholar
  18. 18.
    Nilchiani, R., Hastings, D.E.: Measuring the value of flexibility in space systems: a six-element framework. Syst. Eng. 10(1), 26–44 (2007)CrossRefGoogle Scholar
  19. 19.
    Alsafi, Y., Vyatkin, V.: Ontology-based reconfiguration agent for intelligent mechatronic systems in flexible manufacturing. Robot. Comput. Integr. Manuf. 26(4), 381–391 (2010)CrossRefGoogle Scholar
  20. 20.
    Regulin, D., Schutz, D., Aicher, T., Vogel-Heuser, B.: Model based design of knowledge bases in multi agent systems for enabling automatic reconfiguration capabilities of material flow modules. In: IEEE International Conference on Automation Science and Engineering, pp. 133–140 (2016)Google Scholar
  21. 21.
    Rodriguez, I.B., Drira, K., Chassot, C., Jmaiel, M.: A model-based multi-level architectural reconfiguration applied to adaptability management in context-aware cooperative communication support systems. In: 2009 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture, WICSA/ECSA, pp. 353–356 (2009)Google Scholar
  22. 22.
    Otto, K., Wood, K.L.: Product design: techniques in reverse engineering and new product development, September 2014 (2001)Google Scholar
  23. 23.
    Giffin, M., de Weck, O.L., Bounova, G., Keller, R., Eckert, C., Clarkson, P.J.: Change propagation analysis in complex technical systems. ASME J. Mech. Des. 131, 1–14 (2009)CrossRefGoogle Scholar
  24. 24.
    Clarkson, P.J., Simons, C., Eckert, C.: Predicting change propagation in complex design. J. Mech. Des. 126(5), 788 (2004)CrossRefGoogle Scholar
  25. 25.
    Schuh, G., Riesener, M., Breunig, S.: Design for changeability: incorporating change propagation analysis in modular product platform design. Procedia CIRP 61, 63–68 (2017)CrossRefGoogle Scholar
  26. 26.
    Ottosson, S.: Participation action research. Technovation 23(2), 87–94 (2003)CrossRefGoogle Scholar
  27. 27.
    Blessing, L.T.M., Chakrabarti, A.: DRM, a Design Research Methodology, vol. 1 (2009)CrossRefGoogle Scholar
  28. 28.
    Summers, J.D., Eckert, C.M.: Design research methods: interviewing. In: Workshop in ASME Conference 2013, Portland, Oregan, USA (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Lara Qasim
    • 1
    • 2
    Email author
  • Marija Jankovic
    • 2
  • Sorin Olaru
    • 3
  • Jean-Luc Garnier
    • 1
  1. 1.Thales Technical DirectoratePalaiseau CedexFrance
  2. 2.Laboratoire Génie Industriel, CentraleSupelecGif-sur-yvetteFrance
  3. 3.Laboratoire de Signaux et Systemes, CentraleSupelecGif-sur-yvetteFrance

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