Title page for etd-0923114-153755


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URN etd-0923114-153755
Author Mao-Jung Tsai
Author's Email Address No Public.
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Department Information Management
Year 2014
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Predicting Product Yield of Flexible Copper Clad Laminate Using Data Mining Approach
Date of Defense 2014-07-12
Page Count 61
Keyword
  • FCCL
  • Yield
  • Factor Analysis
  • Regression Analysis
  • Data Mining
  • Abstract Flexible copper clad laminate, which is the major material of flexible print circuit. Decause the mobile devices are becoming smaller, thinner, high temperature resistant, and bend-resistant, the market of 2-layer FCCL is evolving. Yield issue is the main concern of all FCCL manufacturers, which is related to lower cost and higher profit, and it’s the key performance indicator to keep competition.
    This research selects some possible factors that will affect the result of yield from lots of 2 layer FCCL production data. To simplify different factors, we evaluate correlation factors by factor analysis. Then we use data mining technology to observe the significance and co-linearity of every factor and eliminate the factors that are high VIF and non-significant. If the data is an important analysis variable and belongs to class variable, it will be transformed to virtual variable. Finally, we build up a regression model by multi-regression analysis to compare the relationship of key factors and actual yield.
    This research collects all real data from FCCL manufacturer since 2-layer FCCL was released to mass production from 2013 to March, 2014. We compare with the actual result, and the average deviation is 0.523%. This model is reliable, and we believe it will be applicable on real production plan and yield prediction.
    Advisory Committee
  • Wan-Shiou Yang - chair
  • Shih-Chieh Hsu - co-chair
  • San-Yia Hwang - advisor
  • Files
  • etd-0923114-153755.pdf
  • Indicate in-campus at 1 year and off-campus access at 3 year.
    Date of Submission 2014-10-23

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