• DocumentCode
    2641992
  • Title

    Using data mining to improve supplier release stability

  • Author

    Cavaretta, Michael ; Chou, Gloria ; Madani, Bardia

  • Author_Institution
    Res. & Adv. Eng., Ford Motor Co., Dearborn, MI, USA
  • fYear
    2005
  • fDate
    26-28 June 2005
  • Firstpage
    252
  • Lastpage
    256
  • Abstract
    Communications of material requirements between a manufacturer and its supply base is fraught with inefficiencies. Suppliers complain that variation in material quantity requires them to keep extra capacity on hand, as well as preventing optimization of their labor and equipment. The manufacturer experiences issues with instability, also preventing optimization of labor and equipment. This paper proposes using data mining, a series of statistical and artificial intelligence techniques for extracting knowledge from large databases, to identify opportunities for reducing material requirement variation.
  • Keywords
    artificial intelligence; data mining; materials requirements planning; artificial intelligence; data mining; knowledge extraction; manufacturer supply base; material requirements; statistical technique; supplier release stability; supply material quantity; Artificial intelligence; Data mining; Databases; Knowledge management; Manufacturing; Production; Stability analysis; Supply chains; Vehicles; Wikipedia;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
  • Print_ISBN
    0-7803-9187-X
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2005.1548543
  • Filename
    1548543