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Application of Data Mining in Manufacturing Quality Data

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Abstract

Knowledge on product quality is one of the most important knowledge sources throughout the product lifecycle for the efficiency and effectiveness of product design decisions. To provide quality related knowledge, this paper proposed one data mining based knowledge discovery approach. This approach can extract knowledge on product quality from large volume of quality related manufacturing data. The effectiveness of this approach is illustrated and validated by an example adapted from literature. Finally, some conclusions and future works are discussed.
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Dates and versions

hal-02548611 , version 1 (20-04-2020)

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Keqin Wang, Shurong Tong, Benoît Eynard, Lionel Roucoules, Nada Matta. Application of Data Mining in Manufacturing Quality Data. 2007 International Conference on Wireless Communications, Networking and Mobile Computing, Sep 2007, Shanghai, China. pp.5377-5380, ⟨10.1109/WICOM.2007.1318⟩. ⟨hal-02548611⟩
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