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研究生:盧延昇
研究生(外文):Yen-sheng Lu
論文名稱:LCD-TFT製程整合性良率分析
論文名稱(外文):An Integrated Yield Analysis for LCD-TFT Manufacturing Process
指導教授:謝昆霖謝昆霖引用關係
指導教授(外文):Kun-lin Hsieh
學位類別:碩士
校院名稱:南華大學
系所名稱:資訊管理學研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2006
畢業學年度:95
語文別:英文
論文頁數:33
中文關鍵詞:逐步迴歸良率模式類神經網路(ANNs)液晶顯示器(LCDs)
外文關鍵詞:Stepwise regressionArtificial neural networks (ANNs)Liquid crystal displays (LCDs)Yield model
相關次數:
  • 被引用被引用:2
  • 點閱點閱:1010
  • 評分評分:
  • 下載下載:157
  • 收藏至我的研究室書目清單書目收藏:1
  製程改善能力是當前 TFT-LCD 製造商競爭力的決定性因素之一,但直到現今,還沒有任何適當的理論被提出用以改善 TFT-LCD 工業的良率問題,然而經驗證從良率模式所獲得的資訊(例如,domain knowledge 或parameter effect)對於 TFT-LCD 的製造商實能夠提供有用的建議和改善方案,也就是說,良率模式的建構與製程參數的影嚮性,對於 TFT-LCD 產業的良率分析而言,將會是一個必需被重視的課題。
 
  在此篇論文中,我們提出了結合類神經網路與迴歸分析之技術以達成良率模式的建構,並在實例說明中,套用一臺灣臺南科學園區的TFT-LCD 製造商的實際生產資料,用以驗證我們所提出的模式。
  The ability to improve yield in manufacturing process is an important competitiveness determinant for TFT-LCD factories. Until now, no any suitable theories were proposed to address the yield problem in TFT-LCD industry. However, the information (e.g. the domain knowledge or the parameter effect) obtained from the yield model will provide useful recommendations and improvements to those manufacturers. That is, the model construction and parameter effect for yield analysis will be a necessary issue to be addressed.
 
  In this study, we proposed a procedure incorporating the artificial neural networks (ANNs) and stepwise regression techniques to achieve the model construction and parameter effect. Besides, an illustrative case owing to TFT-LCD manufacturer at Tainan Science Park in Taiwan will be applied to verifying our proposed procedure.
Chapter 1 Introduction.......................1
 
Chapter 2 Background Information.......................4
2.1 Stepwise model-building technique.......................4
2.2 Backpropagation Neural Network Model (BPNN).......................8
 
Chapter 3 Proposed approach .......................12
3.1 Step1 Determine the input/output variables of system and collect data.......................13
3.2 Step2 Construct the yield model by using BPNN model.......................14
3.3 Step3 Screen out the effect of all parameters by using stepwise regression analysis.............15
 
Chapter 4 Illustrative example.......................17
4.1 TFT-LCD manufacturing processes introduction.......................17
4.1.1 Array assembly process (Array).......................17
4.1.2 Cell assembly process (Cell).......................17
4.1.3 Module assembly process (Module).......................18
4.2 TFT-LCD array manufacturing process introduction.......................20
4.3 Yield model verification.......................22
 
Chapter 5 Concluding remarks and recommendations.......................29
 
Reference.......................31
 
List of Tables
Table 1. The correlation value for the yield and each parameter.......................23
Table 2. The comparison table for the different structures of BPNN.......................26
 
List of Figures
Figure 1. TFT-LCD manufacturing processes.......................18
Figure 2. The TFT-LCD structural.......................19
Figure 3. TFT-LCD Array manufacturing processes.......................21
Figure 4. The diagram for yield model based on BPNN model.......................25
Figure 5. The comparison diagram for the actual and the predicted yield value.......................27
Darlington, R. B. (1990). Regression and linear models. New York: McGraw-Hill.
 
Hocking, R. R. (1996). Methods and Applications of Linear Models. Regression and the Analysis of Variance. New York: Wiley.
 
Hsieh, K. L., (2001), Process Improvement in the Presence of Qualitative Response by Combining Fuzzy Sets and Neural Networks, Integrated Manufacturing Systems, 12(6-7), pp. 449-462.
 
Hsieh, K. L., (2006), Parameter Optimization of a Multi-response Process for Lead frame Manufacturing by Employing Artificial Neural Networks, International Journal of Advanced Manufacturing Technology (in press)
 
Ko, D. C., Kim, D. H., Kim, B. M. and Choi, J. C., (1998), Methodology of perform design considering workability in metal forming by the artificial neural network and Taguchi method, Journal of Materals Processing Technology, 80-81, pp. 487-492.
 
Lindeman, R. H., Merenda, P. F., & Gold, R. (1980). Introduction to bivariate and multivariate analysis. New York: Scott, Foresman, & Co.
 
Liu, J. Z., Ma, K., Cham, W. K. and Chang, M. M. Y., (2000), Two-layer assignment method for online Chinese character recognition, IEE Proceedings- Vision, Image and Signal Processing, 147(1), pp. 47-54.
 
Morrison, D. F. (1990). Multivariate statistical methods. (3rd Ed.). New York: McGraw-Hill.
 
Neter, J., Wasserman, W., & Kutner, M. H. (1985). Applied linear statistical models: Regression, analysis of variance, and experimental designs. Homewood, IL: Irwin.
 
Neural Ware, Inc., (1990), Neural Works Professional II/Plus and NeuralWorks Exporer, Penn Center West: Neural Ware, Inc.
 
Phadke, M. S., (1986), Quality Engineering Using Robust Design. Prentice-Hall, Englewood Cliffs, New Jersey.
 
Peace, G. S., (1993), Taguchi methods: A Hands-on Approach, Addison-Wesley.
 
Pedhazur, E. J. (1982). Multiple regression in behavioral research (2nd ed.). New York: Holt, Rinehart, & Winston.
 
Rumelhart, D. E., Hinton, G. E. and Williams, R. J., (1986), Learning internal representations by error propagation, Parallel Distributed Processing: Explorations in the Microstructure of cognition, Edited by Rumelhart, D. E., McClelland, J. L., MIT Press, Cambridge, MA, 1, pp.318-362.
 
Singer, P., (1994), Flat panel displays: an interesting test case for the U.S., Semiconductor International, 17(7), pp. 78-88.
 
Stevens, J. (1986). Applied multivariate statistics for the social sciences. Hillsdale, NJ: Erlbaum.
 
Su, C. T., Yang, T. and Wang, P. S., (2004), An optimal yield mapping approach for liquid crystal displays, Journal of Quality, 11(4), pp.283-293.
 
Younger, M. S. (1985). A first course in linear regression (2nd ed.). Boston: Duxbury Press.
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