| 研究生: |
劉清衍 Liu, Ching-Yen |
|---|---|
| 論文名稱: |
液晶面板的瑕疵之關聯分析 Association Analysis of the Defects in TFT-LCD Panels |
| 指導教授: |
翁慈宗
Wong, Tzu-Tsung |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業與資訊管理學系碩士在職專班 Department of Industrial and Information Management (on the job class) |
| 論文出版年: | 2016 |
| 畢業學年度: | 104 |
| 語文別: | 中文 |
| 論文頁數: | 83 |
| 中文關鍵詞: | 關聯規則 、瑕疵 、資料探勘 、面板 |
| 外文關鍵詞: | association rules, defect, data mining, TFT-LCD |
| 相關次數: | 點閱:150 下載:5 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
近年來,由於大陸持續興建新世代面板廠,不斷擴充產能,在全球各類液晶顯示器需求下滑的情況下,面板價格持續下跌。為了對抗紅潮來襲,台灣的面板製造商的除了持續研發新產品與力求產品差異化外,也著重在穩定與提高產品品質。
本研究使用關聯分析,建構模型分析面板瑕疵間的相關性,實驗結果顯示,透過該產品最常發生的4個瑕疵,從一條或一條以上的規則中,可以找出面板上其他可能存在的罕見瑕疵,使檢測人員能快速且正確的檢測瑕疵。另外,以班別與機台為屬性值所作的實驗顯示,結果可以作為生產線的管理參考。
In recent years, many companies in China continued to build new-generation TFT-LCD plants for expanding production capacity. The growth of all kinds of liquid crystal display global demand has been slowed down, and the price of a panel continues to fall. The TFT-LCD makers in Taiwan pay their attentions on developing new products, differentiating the characteristics of products, and improving product quality to combat the red-tide strikes. This study proposes a method to analyze the association among the defects on TFT-LCD panels. There are four common defects in TFT-LCD panels, and the resulting rules provide the associations between common and rare detects. Inspectors can use the association rules to improve the detection efficiency and accuracy of defects by reducing their missing rates, and hence the quality of panels is enhanced. The experimental results on shifts and machines also present useful guidelines for managing the operations of production lines.
中文
王君毅,360°科技,2007年9月13日,取自:http://www.digitimes.com.tw
翁慈宗. (2009).資料探勘的發展與挑戰.科學發展期刊, 442, 34-37.
潘儀君。《產品責任與產品責任保險以消費者保護法為中心探討二者互動之關係》。國立臺灣大學法律學系研究所,1998。
英文
Agrawal, R. and Srikant, R. (1994), Fast algorithms for mining association rules. In Proceedings 20th VLDB Conference, 487-499.
Agrawal, R., Imieliński, T., and Swami, A. (1993), Mining association rules between sets of items in large databases. In Proceedings of the ACM SIGMOD Conference on Management of Data, 207-216.
Ahmed, S. R. (2004). Applications of data mining in retail business. In International Conference on Information Technology: Coding and Computing, 455-459.
Bhattacharyya, S., Jha, S., Tharakunnel, K., and Westland, J. C. (2011), Data mining for credit card fraud: A comparative study. Decision Support Systems, 50(3), 602-613.
Chao, J. C., Iravani, S. M., and Savaskan, R. C. (2009), Quality improvement incentives and product recall cost sharing contracts. Management Science, 55(7), 1122-1138.
Cheng, Y. and Li, Q. (2015), GA‐based multi-level association rule mining approach for defect analysis in the construction industry. Automation in Construction, 51, 78-91.
Czibula, Q., Marian, Z., and Czibula, I. G. (2014), Software defect prediction using relational association rule mining. Information Sciences, 264, 260-278.
Duan, L., Street, W. N., and Xu, E. (2011), Healthcare information systems: Data mining methods in the creation of a clinical recommender system. Enterprise Information Systems, 5(2), 169-181.
Grossman, R., Kasif, S., Moore, R., Rocke, D., and Ullman, J. (1999), Data mining research: Opportunities and challenges. A Report of three NSF workshops on Mining large, Massive, and Distributed data.
Han, J. and Kamber M. (2000), Data mining: concepts and techniques. Berlin: Morgan Kaufmann Publishers.
Kim, H. S., Lee, Y. J., Lee, S. H., Kang, T. G., Lee, S. H., and Kim, W. J. (2001), U.S. Patent No. 6,175,396. Washington, DC: U.S. Patent and Trademark Office.
Kim, W. S., Kwak, D. M., Song, Y. C., Choi, D. H., and Park, K. H. (2004), Detection of spot-type defects on liquid crystal display modules. Key Engineering Materials, 270, 808-813.
Koc, L., Mazzuchi, T. A., and Sarkani, S. (2012). A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier. Expert Systems with Applications, 39(18), 13492-13500.
Kusiak, A. and Kurasek, C. (2001), Data mining of printed-circuit board defects. IEEE Transactions on Robotics and Automation, 17(2), 191-196.
Lee, C. K. H., Choy, K. L., Ho, G. T., Chin, K. S., Law, K. M. Y., and Tse, Y. K. (2013). A hybrid OLAP-association rule mining based quality management system for extracting defect patterns in the garment industry. Expert Systems with Applications, 40(7), 2435-2446.
Lin, J. T., Hong, I. H., Wu, C. H., and Wang, K. S. (2010). A model for batch available-to-promise in order fulfillment processes for TFT-LCD production chains. Computers & Industrial Engineering, 59(4), 720-729.
Lu, C. J. and Tsai, D. M. (2004). Defect inspection of patterned thin film transistor-liquid crystal display panels using a fast sub-image-based singular value decomposition. International Journal of Production Research, 42(20), 4331-4351.
Mollazade, K., Omid, M., and Arefi, A. (2012). Comparing data mining classifiers for grading raisins based on visual features. Computers and Electronics in Agriculture, 84, 124-131.
Nakashima, K. (1994). Hybrid inspection system for LCD color filter panels. Proceedings of the 10th International Conference on Instrumentation and measurement Technology, Hamamatsu, 689-692.
Oh, J. H., Kwak, D. M., Lee, K. B., Song, Y. C., Choi, D. H., and Park, K. H. (2004). Line defect detection in TFT-LCD using directional filter bank and adaptive multilevel thresholding. Key Engineering Materials, 270, 233-238.
Park, N. K. and Yoo, S. I. (2009). Evaluation of TFT-LCD defects based on human visual perception. Displays, 30(1), 1-16.
Park, J. S., Chen, M. S., and Yu, P. S. (1997). Using a hash-based method with transaction trimming for mining association rules. IEEE Transactions on Knowledge and Data Engineering, 9(5), 813-825.
Savasere, A., Omiecinski, E. R., and Navathe, S. B. (1995). An efficient algorithm for mining association rules in large databases. In Proceedings 21th VLDB Conference, 432-443.
校內:2021-12-31公開