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    National Tsing Hua University Institutional Repository > 工學院  > 工業工程與工程管理學系 > 會議論文  >  Developing data mining methods for wafer bin map clustering and the empirical study in a semiconductor manufacturing FAB


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/46431


    Title: Developing data mining methods for wafer bin map clustering and the empirical study in a semiconductor manufacturing FAB
    Authors: Chen-Fu Chien;Qiao-Wen Liu
    教師: 簡禎富
    Date: 2001
    Publisher: International Conference on Modern Industrial Engineering and Engineering Management in New Century (IE&EM'2001)
    Relation: International Conference on Modern Industrial Engineering and Engineering Management in New Century (IE&EM'2001), Tianjin, China, August 10-12, 2001, pp. 581-587
    Keywords: Wafer bin map
    Neural network
    Data mining
    Defect diagnosis
    Decision analysis
    Abstract: The semiconductor industry has been one of the most important components of the Taiwan manufacturing industries. Because of the complex fabrication processes and the cost resulted from defects, analyzing wafer bin maps and mining potentially useful information from large such database become increasingly important in both research and application for semiconductor manufacturing. We develop a hybrid approach that combines spatial statistics and ART neural network for wafer bin map clustering to assist the product engineers in narrowing possible causes of manufacturing defects. We conducted an empirical study in a semiconductor fab and the results showed the practical viability of this approach.
    URI: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/46431
    Appears in Collections:[工業工程與工程管理學系] 會議論文

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