JSW 2008 Vol.3(8): 73-79 ISSN: 1796-217X
doi: 10.4304/jsw.3.8.73-79
doi: 10.4304/jsw.3.8.73-79
Using Data Mining in MURA Graphic problems
Wen-Hsing Kao, Jason C. Hung and Victoria Hsu
Graduate Institute of Information Technology, The Overseas Chinese Institute of Technology, Taichung, Taiwan
Abstract—The MURA phenomenon will result lots of problems in Photomask and TFT-LCD industries as well. In this paper, we designed and developed a MURA related association rules which suitable for the MURA model requirements, and we named MURA Risk rating system. Our purpose is to figure out the effective application of data mining algorithms in monitoring and control of complex Large Area Photomask systems. By combining the Data Mining into MURA risk management. It could be suitable not only for every Photomask company but also companies facing to the MURA problems. And through our scheme and MURA risk rating system, we can shorten the time and reduce the MURA problems. It could also help them to cut down their manufacturing cost as well as promote the quality of their products.
Index Terms—Large Photomask, MURA, Data Mining, Data Mining application
Abstract—The MURA phenomenon will result lots of problems in Photomask and TFT-LCD industries as well. In this paper, we designed and developed a MURA related association rules which suitable for the MURA model requirements, and we named MURA Risk rating system. Our purpose is to figure out the effective application of data mining algorithms in monitoring and control of complex Large Area Photomask systems. By combining the Data Mining into MURA risk management. It could be suitable not only for every Photomask company but also companies facing to the MURA problems. And through our scheme and MURA risk rating system, we can shorten the time and reduce the MURA problems. It could also help them to cut down their manufacturing cost as well as promote the quality of their products.
Index Terms—Large Photomask, MURA, Data Mining, Data Mining application
Cite: Wen-Hsing Kao, Jason C. Hung and Victoria Hsu, " Using Data Mining in MURA Graphic problems," Journal of Software vol. 3, no. 8, pp. 73-79, 2008.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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