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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/4757

    Title: A novel manufacturing defect detection method using association rule mining techniques
    Authors: W. C. Chen;S. S. Tseng;C. Y. Wang
    Contributors: Department of Information Science and Applications
    Keywords: Association rule mining;Defect detection;Interestingness measurement;Manufacturing defect detection problem
    Date: 2005-11
    Issue Date: 2009-11-30 16:03:26 (UTC+8)
    Publisher: Asia University
    Abstract: 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.
    Relation: Expert Systems with Applications 29(4):379-390
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

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