By Topic

Using data mining to improve supplier release stability

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Cavaretta, M. ; Res. & Adv. Eng., Ford Motor Co., Dearborn, MI, USA ; Chou, G. ; Madani, B.

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.

Published in:

Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American

Date of Conference:

26-28 June 2005