臺灣博碩士論文加值系統

目前半導體業在長晶（Crystal growth）製程中最常檢驗的是氧化造成的疊差（Oxidation Induce Stacking Fault, 簡稱OISF），基本上OISF現象可分為棒狀及半月形兩種，這兩種OISF現象主要是在長晶及矽晶柱後製程中產生。半導體業對於OISF影像中棒狀或半月形之個數密度量測（單位面積內垂直水平個數總合），一般是透過光學顯微儀器放大影像，對員工做特殊訓練後以人工目測求得，計算過程中消耗大量的人力資源與時間。利用自動視覺技術於OISF之檢測，可以減少人力資源與時間之浪費，且無人工作業疲勞所造成的誤判、標準不一的主觀因素，同時可提高檢驗品質、降低生產成本。
本研究針對客戶要求做特殊處理的OISF檢驗，採用傳統Sobel邊緣偵測運算子（Sobel operator）與全尺寸小波轉換（Wavelet frame）兩種方法來分離OISF中棒狀與半月形之垂直與水平邊緣，找出垂直水平能量值並求得垂直水平個數。對於一般OISF影像垂直水平個數之計算，其實驗誤差百分比在5%以內。對於高重疊OISF影像垂直水平個數之計算，因重疊部份為製程不可控制因素，而容易產生較高的實驗誤差百分比，因此本研究透過邊緣點數之臨界值設定，有效的選取影像中垂直水平邊緣重疊的部份，提高計算垂直水平個數的精確度，將實驗誤差百分比控制在3%以內。

Oxidation Induce Stacking Fault (OISF) is frequently inspected in the crystal growing process of semiconductor industry. The appearance of OISF has “bar” and “half-moon” types that are mainly produced in crystal growth and silicon crystal post-manufacturing process. OISF image are generally enlarged by an optical electron microscope, and the density measure (total number of vertical and horizontal OISFs in a unit area) is manually obtained by a specially trained inspector. Number counting is a tiresome task, and very subjective from inspector to inspector. In this research we use machine vision to automatically compute the density measures of both “bar” and “half-moon” OISFs in a crystal surface. The inspection quality and time can be greatly improved with the automated visual inspection system.
This research uses Sobel edge operator and wavelet frame to separate vertical and horizontal edges of “bar” and “half-moon” OISFs in a image. The number of horizontal and vertical OISFs in each separated image can be easily evaluated accordingly. Experimental results have shown that the average error of the proposed method is smaller than 5%, which is competitive with human inspectors.

中文摘要 ……………………………………………………………………Ⅰ
英文摘要 ……………………………………………………………………Ⅱ
誌謝 …………………………………………………………………………Ⅲ
目錄 …………………………………………………………………………IV
表目錄 ………………………………………………………………………Ⅵ
圖目錄 ………………………………………………………………………Ⅷ
第一章 緒論…………………………………………………………………1
1.1 研究動機與目的 ………………………………………………………1
1.2 研究方法簡介 …………………………………………………………2
第二章 矽晶柱製造過程……………………………………………………5
2.1 簡介 ……………………………………………………………………5
2.2 矽晶柱成長之製程 ……………………………………………………5
2.3 矽晶柱之後處理 ………………………………………………………7
2.4 工業界OISF檢驗 ………………………………………………………9
第三章 研究方法……………………………………………………………12
3.1 研究方法概述 …………………………………………………………12
3.2 Sobel邊緣偵測運算子（Sobel operator）…………………………15
3.3 傳統之小波轉換（Wavelet transform）……………………………31
3.4 不抽樣之小波轉換（Wavelet frame）………………………………32
第四章 實驗結果與討論……………………………………………………42
4.1 OISF之個數密度值檢測 ………………………………………………42
4.1.1 人工OISF之個數密度值 ……………………………………………42
4.1.2 自然OISF之個數密度值 ……………………………………………43
4.2 實驗結果之結論 ………………………………………………………58
第五章 結論與建議…………………………………………………………60
參考文獻 ……………………………………………………………………63
附錄一 小波基底之高通與低通濾波器小波係數值………………………65
附錄二 不抽樣小波轉換不受位移影響之結果……………………………66
附錄三 傳統小波轉換受位移影響之結果…………………………………67
附錄四 高重疊性之棒狀圖與半月形圖之最大邊緣點數搜尋圖…………68
附錄五 一般OISF影像與高重疊OISF影像之待測樣本……………………70
附錄六 程式說明……………………………………………………………90

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蔣政輝，民國89年，“小波轉換於自動表面瑕疵檢測與圖形比對的應用”，碩士論文，元智大學工業工程與管理研究所。
蕭缽，民國88年，“應用小波轉換於表面瑕疵檢測”，碩士論文，元智大學工業工程研究所。
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