近年來由於半導體產業的快速發展，對於製程技術的要求越來越高，且良率亦是製造業中重要的獲利指標之一，如何提高製程的良率是一項非常重視的議題。在半導體每道重要製程後所進行之晶圓缺陷圖樣檢測中發現，缺陷圖樣與製程問題間有著密不可分的關係，因此晶圓上的缺陷圖樣資料成為提供工程師改善製程良率問題的重要線索，有鑑於此，本研究提出一能夠有效辨識晶圓缺陷圖樣之架構與方法論，並針對半導體廠所關心之晶圓缺陷圖樣包括曲線型、直線型、戒指型、區域型、放射型、重複型與晶片邊緣型共七種缺陷圖樣進行分析。本研究之分析步驟以半導體廠實際所收集到的缺陷資料轉換成影像方式呈現，並利用影像處理的技術濾除隨機性的缺陷點，接著將留在晶圓上的系統性缺陷進行分群的動作，並擷取分群後每一群缺陷所涵蓋之最小矩形區域，以利後續特徵值的擷取能更準確。接著為本研究分析之核心部份，將所擷取到的缺陷所形成的矩型區域，進行二維的小波轉換，並進一步計算每一頻帶之小波能量特徵值，當作本研究缺陷圖樣之特徵值，將特徵值轉化為特徵向量，並將其投射至特徵空間，利用階層式聚合演算法所形成的七個群聚之距離，並將其分類到距離最近的群聚，以有效辨識出七種缺陷圖樣。本研究之實證結果發現，針對七種缺陷圖樣之辨識正確率達到95%，因此本研究所提出之辨識分析方法具有相當的準確性，同時能夠輔助工程師快速有效率的辨識缺陷圖樣以改善半導體良率問題。

In recent years, the semiconductor industry has been a high-growth business. Yield improvement is more and more important for the process of semiconductor manufacturing since it is an important element to ensure the profitability. Defect spatial pattern impedes yield and it can reveal the root cause of the occurred defects. For this consideration, this research intends to develop a defect spatial pattern methodology for yield enhancement. Defect spatial patterns are classified into seven categories including Curve Type, Line Type, Local Type, Ring Type, Radial Type, Repeat Type and Die Edge Type. To achieve the purpose of recognition, the coordinate data are transformed into image format and image processing techniques are applied to eliminate the random defects. Clustering methods are then applied to locate systematic defects. Minimum rectangle area method is collected cluster defects for further analysis. The feature extraction procedure in this research is adopted by wavelet transform algorithm. By setting feature vectors into feature space and applying hierarchical agglomerative algorithm to clustering, the result is expected to reach the goal of description and classification. The proposed methodology is verified with industrial data from a famous semiconductor company in Taiwan. The average accuracy of recognition is 95%.The experimental results show that this method can successfully recognize the defect spatial patterns and enhance the yield in semiconductor manufacturing.

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