標題: A novel manufacturing defect detection method using association rule mining techniques
作者: Chen, WC
Tseng, SS
Wang, CY
資訊工程學系
Department of Computer Science
關鍵字: association rule mining;defect detection;interestingness measurement;manufacturing defect detection problem
公開日期: 1-十一月-2005
摘要: In recent years, manufacturing processes have become more and more complex, and meeting high-yield target expectations and quickly identifying root-cause machinesets, the most likely sources of defective products, also become essential issues. In this paper, we first define the root-cause machineset identification problem of analyzing correlations between combinations of machines and the defective products. We then propose the Root-cause Machine Identifier (RMI) method using the technique of association rule mining to solve the problem efficiently and effectively. The experimental results of real datasets show that the actual root-cause machinesets are almost ranked in the top 10 by the proposed RMI method. (c) 2005 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2005.06.004
http://hdl.handle.net/11536/13107
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2005.06.004
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 29
Issue: 4
起始頁: 807
結束頁: 815
顯示於類別:期刊論文


文件中的檔案:

  1. 000232757700009.pdf