Cellular manufacturing performance improvement using data mining techniques
by Mahammad Aloudat, Ali K. Kamrani, Emad Abouel Nasr
International Journal of Knowledge Management Studies (IJKMS), Vol. 2, No. 4, 2008

Abstract: This paper examines cell quality performance improvement through the integration of data mining using Artificial Neural Network (ANN) techniques and cellular manufacturing. The aim of this paper is to study and predict the factors that impact quality product in cellular manufacturing, such as used material, material complexity, operation type (lathe, mill, thread, groove, bore, etc.), machine, machinist and quantity to improve cell performance. The outcome suggests improvement in the part processing sequence, machining process capability, formation of family products, design, the machine operator performance and work schedule in order to improve the machine performance in cellular manufacturing.

Online publication date: Tue, 29-Jul-2008

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Management Studies (IJKMS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com