博碩士論文 107521049 詳細資訊




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姓名 吳嘉峻(Chia-Chun Wu)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 基於特徵分析識別晶圓圖刮痕樣態
(Through Feature based Analysis to Recognize Wafer Map Scratch Pattern)
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摘要(中) 本篇論文中以特徵分析的方式判別晶圓圖的刮痕錯誤樣態,透過霍夫變換尋找晶圓圖上直線及弧線的缺陷。我們所使用的實際晶圓為台積電所提供的WM-811K晶圓資料庫,而錯誤樣態可分以下九種,Center、Donut、Scratch、Edge-Ring、Edge-Loc、Loc、Near-Full、Random、None。而本篇論文為判別Scratch的部分。
首先,我們將晶圓圖進行降噪的動作,將晶圓圖上有離散的瑕疵點移除,把相較明顯的群聚點留於晶圓圖。而在降噪後將晶圓圖輸入圖轉換為灰階圖案,並且將晶圓圖調整縮放至統一格式陣列,使之於霍夫變換時便於參數設定。
接著,在找尋晶圓圖上直線的樣態時,我們採用極座標系的方程式而非直線方程式,避免當直線在垂直於平面座標系X軸時,斜率為無限大而無法計算。而在找尋晶圓圖上弧線的樣態時,則採用橢圓方程式進行計算,藉由這兩種公式套用於霍夫變換演算法進行晶圓圖上刮痕圖案的尋找,達到以基於特徵分析的方式識別晶圓圖刮痕樣態。
最後以這兩種霍夫變換的方式識別刮痕樣態,在WM-811K晶圓圖資料庫中取部分晶圓圖做測試,並以Accuracy、Precision、Recall的數值表現來顯示本論文模型的判斷準確度。
摘要(英) In this paper, we use feature analysis to identify the scratch errors of the wafer map, and use the Hough transform to find the defects of straight lines and arcs on the wafer map. The actual wafer we used is the WM-811K wafer database provided by TSMC, and the error patterns can be divided into the following nine types: Center, Donut, Scratch, Edge-Ring, Edge-Loc, Loc, Near-Full, Random, None. And this paper is the part to distinguish Scratch.
First, we perform a noise reduction operation on the wafer map, remove discrete defects on the wafer map, and leave the more obvious cluster points on the wafer map. After the noise is reduced, the wafer map input map is converted into a gray-scale pattern, and the wafer map is adjusted and scaled to a uniform format array, so that it is convenient for parameter setting during Hough transformation.
Then, when looking for the shape of the straight line on the wafer map, we use the equation of the polar coordinate system instead of the linear equation to avoid that when the straight line is perpendicular to the X axis of the plane coordinate system, the slope is infinite and cannot be calculated. When looking for the shape of the arc on the wafer map, the ellipse equation is used to calculate. By applying these two formulas to the Hough transform algorithm to find the scratch pattern on the wafer map, it can be achieved based on feature analysis. Ways to identify the scratches on the wafer map.
Finally, the scratch patterns are identified by these two Hough transform methods, and part of the wafer map is taken from the WM-811K wafer map database for testing, and the numerical performance of Accuracy, Precision, and Recall is used to show the model of this paper. Judgment accuracy.
關鍵字(中) ★ 晶圓圖
★ 錯誤樣態辨識
★ 特徵分析
關鍵字(英) ★ Wafer map
★ Pattern recognition
★ Feature based analysis
論文目次 中文摘要 i
Abstract ii
致謝 iii
目錄 iv
圖目錄 v
表目錄 vii
第一章 緒論 1
1-1 前言 1
1-2 研究動機 2
1-3 研究方法 3
1-4 論文架構 4
第二章 預備知識 5
2-1文獻探討 5
2-2 基於特徵辨識晶圓圖 7
2-3 群聚演算法DBSCAN 8
第三章 晶圓圖之刮痕樣態檢測 12
3-1 霍夫變換檢測 12
3-2 晶圓圖之資料預處理 15
3-3 晶圓圖之刮痕樣態辨識流程 21
第四章 模型檢測與實驗結果 22
4-1 WM-811K原始刮痕資料分析 22
4-2 刮痕樣態檢測結果 25
4-3 混合樣態刮痕檢測 29
4-4 刮痕樣態辨識率評估 29
第五章 結論 39
參考文獻 40
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[2] Ming-Ju Wu, Jyh-Shing Roger Jang, and Jui-Long Chen, “Wafer Map Failure Pattern Recognition and Similarity Ranking for Large-Scale Data Sets”, IEEE Transactions on Semiconductor Manufacturing, Vol 28, pp. 1-12, Feb. 2015.

[3] Takeshi Nakazawa, and Deepak V. Kulkarni, “Wafer Map Defect Pattern Classification and Image Retrieval Using Convolutional Neural Network”, IEEE Transaction on Semiconductor Manufacturing, Vol 31, pp. 309-314, May. 2018.

[4] Mengying Fan, Qin Wang, and Ben van der Waal, “Wafer defect patterns recognition based on OPTICS and multi-label classification”, IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), pp. 912-915, Oct. 2016.

[5] Tsutomu Ishida, Izumi Nitta, Daisuke Fukuda, and Yuzi Kanazawa, “Deep Learning-Based Wafer-Map Failure Pattern Recognition Framework”, International Symposium on Quality Electronic Design (ISQED), pp. 291-297, Apr. 2019.

[6] 呂東穎, “Applications of Wafer Map Partition Analysisis to Enhance the Salient Pattern Identification”, 碩士論文, 中央大學, 2019.



[7] Katherine Shu-Min Li,Peter Yi-Yu Liao,Ken Chau-Cheung Cheng,Leon Li-Yang Chen,Sying-Jyan Wang,Andrew Yi-Ann Huang;Leon Chou,Gus Chang-Hung Han,Jwu E. Chen,Hsin-Chung Liang and Chung-Lung Hsu, “Hidden Wafer Scratch Defects Projection for Diagnosis and Quality Enhancement”, IEEE Transactions on Semiconductor Manufacturing, Feb. 2021.

[8] Tsutomu Ishida,Izumi Nitta,Daisuke Fukuda and Yuzi Kanazawa , “Deep Learning-Based Wafer-Map Failure Pattern Recognition Framework”, 20th International Symposium on Quality Electronic Design (ISQED) , April.2019 .

[9] Richard O. Duda, Peter E. Hart , “Use of the Hough transformation to detect lines and curves in pictures ”, Communications of the ACM, January.1972 .

[10] Bing Liu, “A Fast Density-Based Clustering Algorithm for Large Databases”, International Conference on Machine Learning and Cybernetics, pp. 996-1000, Aug. 2006.

[11] Cheng Hao Jin, Hyuk Jun Na, Minghao Piao, Gouchol Pok, and Keun Ho Ryu, “A Novel DBSCAN-Based Defect Pattern Detection and Classification Framework for Wafer Bin Map”, IEEE Transactions on Semiconductor Manufacturing, Vol. 32, pp. 286-292, May. 2019.
指導教授 陳竹一(Jwu-E Chen) 審核日期 2021-7-16
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