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
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;
Conference_Titel :
Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
Print_ISBN :
0-7803-9187-X
DOI :
10.1109/NAFIPS.2005.1548543