Title: A novel manufacturing defect detection method using data mining approach
Authors: Chen, WC
Tseng, SS
Wang, CY
資訊工程學系
Department of Computer Science
Issue Date: 2004
Abstract: In recent years, the procedure of manufacturing has become more and more complex. In order to meet high expectation on quality target, quick identification of root cause that makes defects is an essential issue. In this paper, we will refer to a typical algorithm of mining association rules and propose a novel interestingness measurement to provide an effective and accurate solution. First, the manufacturing defect detection problem of analyzing the correlation between combinations of machines and the result of defect is defined. Then, we propose an integrated processing procedure RMI (Root cause Machine Identifier) to discover the root cause in this problem. Finally, the results of experiments show the accuracy and efficiency of RMI are both well with real manufacturing cases.
URI: http://hdl.handle.net/11536/27203
ISBN: 3-540-22007-0
ISSN: 0302-9743
Journal: INNOVATIONS IN APPLIED ARTIFICIAL INTELLIGENCE
Volume: 3029
Begin Page: 77
End Page: 86
Appears in Collections:Conferences Paper