Application of Measurement-Based AHP to Product-Driven System Control

  • William Derigent
  • Alexandre Voisin
  • André Thomas
  • Sylvain Kubler
  • Jérémy Robert
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 694)

Abstract

This paper presents an application of the measurements-based AHP to define a two-stage algorithm for product-driven systems control, in case of an unexpected event. This algorithm is made of two stages: the first one aims at defining which kind of strategy the product should adopt (wait¸ react by itself or switch back to centralized mode) while the second one helps to choose the most appropriate resource able to fulfil the product requirements. The methodology is detailed on a simple case study.

Keywords

Product-driven systems Resource allocation Measurement-based AHP 

References

  1. 1.
    McFarlane, D., Giannikas, V., Wong, A.C., Harrison, M.: Product intelligence in industrial control: theory and practice. Annu. Rev. Control 37(1), 69–88 (2013)CrossRefGoogle Scholar
  2. 2.
    Meyer, G.G., Främling, K., Holmström, J.: Intelligent products: a survey. Comput. Ind. 60(3), 137–148 (2009)CrossRefGoogle Scholar
  3. 3.
    Pannequin, R., Morel, G., Thomas, A.: The performance of product-driven manufacturing control: an emulation-based benchmarking study. Comput. Ind. 60(3), 195–203 (2009)CrossRefGoogle Scholar
  4. 4.
    Borangiu, T., Răileanu, S., Berger, T., Trentesaux, D.: Switching mode control strategy in manufacturing execution systems. Int. J. Prod. Res. (2014). doi: 10.1080/00207543.2014.935825 Google Scholar
  5. 5.
    Lopez, P., Roubellat, F.: Ordonnancement de la production. Hermès Science Publications (2001)Google Scholar
  6. 6.
    Trentesaux, D., Dindeleux, R., Tahon, C.: A multicriteria decision support system for dynamic task allocation in a distributed production activity control structure. Int. J. Comput. Integr. Manuf. 11(1), 3–17 (1998)Google Scholar
  7. 7.
    Ounnar, F., Ladet, P.: Managing breakdowns machines: a Petri Nets model and a decision-making process. J. européen des systèmes automatisés 33(8–9), 977–994 (1999)Google Scholar
  8. 8.
    Saaty, T.L.: How to make a decision: the analytic hierarchy process. Eur. J. Oper. Res. 48(1), 9–26 (1990)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Pach, C., et al.: An effective potential field approach to FMS holonic heterarchical control. Control Eng. Pract. 20(12), 1293–1309 (2012)Google Scholar
  10. 10.
    Zbib, N., et al.: Heterarchical production control in manufacturing systems using the potential fields concept. J. Intell. Manuf. 23(5), 1649–1670 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • William Derigent
    • 1
  • Alexandre Voisin
    • 1
  • André Thomas
    • 1
  • Sylvain Kubler
    • 2
  • Jérémy Robert
    • 2
  1. 1.Université de Lorraine, CRAN, UMR 7039CedexFrance
  2. 2.Interdisciplinary Centre for Security, Reliability & Trust, University of LuxembourgEsch-sur-AlzetteLuxembourg

Personalised recommendations