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  • 标题:Applying Data Mining Techniques for Optimize MURA Graphic Process
  • 本地全文:下载
  • 作者:Wen-Hsiang Shen ; Wen-Hsing Kao
  • 期刊名称:Journal of Emerging Trends in Computing and Information Sciences
  • 电子版ISSN:2079-8407
  • 出版年度:2017
  • 卷号:8
  • 期号:1
  • 页码:10-16
  • 出版社:ARPN Publishers
  • 摘要:The making of large area TFT-LCD mask starts from writing computer-aided design electronic circuit onto quartz blanks and then goes through developing, etching and cleaning processes for final products. MURA is a phenomenon that is caused by uneven brightness on monitors. This research focuses on the improvement of MURA issue solutions. This paper produces an integrated mask vector drawing which includes customer graphics, barcode, mask title, mask serial number, manufacturer name and manufactured date. According to this drawing, we can simulate the overlap areas of writing segments and then obtain a similar writing way of actual writers. It contributes to the shortening of MURA adjusting time during graphic processing procedure and creates an artificial intelligence module for forecasting MURA adjustment risk. By applying this particular module, one can predict the risk of MURA adjustment and prevent it from reaching high-risk graphic area so that the MURA issues can be reduced.
  • 关键词:MURA; TFT-LCD; mask; data mining.
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