• DocumentCode
    2306977
  • Title

    Preference and causal fuzzy models for manager´s decision aiding in industrial performance improvement

  • Author

    Montmain, Jacky ; Clivillé, Vincent ; Berrah, Lamia ; Mauris, Gilles

  • Author_Institution
    Lab. de Genie Inf. et d´´Ing. de la Production, Ecole des Mines d´´Ales, Nîmes, France
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The design and use of Performance Measurement Systems (PMS´s) for industrial improvement and control have received considerable attention in recent years. Indeed, industrial performances are now defined in terms of numerous and multi-level criteria to be synthesized for overall improvement purposes. This article is a contribution to the decision-maker´s information needs for optimizing the improvement of an overall performance versus the allocated resources and for choosing the right actions in order to achieve the required overall performance. The latter is decomposed into elementary performances according to decision-makers´ preferences represented by a fuzzy integral aggregation. The causes-effects links between possible actions and performances are represented by a fuzzy ordinal influence model. The proposed fuzzy models are both applied for improvement actions selection on a case study submitted by a company manufacturing kitchens and bathrooms.
  • Keywords
    decision making; decision support systems; fuzzy logic; performance evaluation; PSM; causal fuzzy model; decision making; decision support systems; fuzzy integral aggregation; fuzzy ordinal influence model; industrial performance improvement; manager decision aiding; performance measurement system; resource allocation; Biological system modeling; Companies; Fuzzy sets; Knowledge engineering; Manufacturing; Optimization; Productivity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-6919-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2010.5584303
  • Filename
    5584303