• DocumentCode
    695424
  • Title

    A Collaborative Manufacturing Collective

  • Author

    Dozier, Ken ; Chang, David

  • Author_Institution
    Western Res. Applic. Center, Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2015
  • fDate
    5-8 Jan. 2015
  • Firstpage
    3851
  • Lastpage
    3859
  • Abstract
    The extent of collaboration among the companies in a manufacturing network impacts the parametric fluctuations in the network. This is displayed explicitly by the form of the network´s normal modes. By gradually increasing the number of companies that actively collaborate, it is possible to see how the form of the normal modes changes. Initial understanding of this normal mode´s resonant damping was developed using a LOGICS (Learning Object Game Immersed Complex Systems) simulation. A traditional fluctuation-plagued supply chain was transformed into an efficient collaborative manufacturing collective. The improvement is achieved while still honoring the desire of individual companies not to directly share what might be considered proprietary information with another company. The method is extendable and should be applicable to more complex adaptive cloud-coordinated manufacturing networks in which efficiency is obtained by system-wide LOGICS-based feedback to individual companies.
  • Keywords
    cloud computing; manufacturing data processing; supply chain management; collaborative manufacturing; complex adaptive cloud-coordinated manufacturing networks; fluctuation-plagued supply chain; learning object game immersed complex systems simulation; system-wide LOGICS-based feedback; Collaboration; Companies; Dispersion; Equations; Manufacturing; Supply chains; collaborative; complex systems; manufacturing; networks; supply chain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences (HICSS), 2015 48th Hawaii International Conference on
  • Conference_Location
    Kauai, HI
  • ISSN
    1530-1605
  • Type

    conf

  • DOI
    10.1109/HICSS.2015.462
  • Filename
    7070281