簡易檢索 / 詳目顯示

研究生: 呂信億
Hsin-I Lu
論文名稱: 應用X射線電腦斷層掃瞄於BGA檢測之最佳化
The Optimization for X-Ray Computer Tomography on BGA Inspection
指導教授: 林士傑
Shin-Chieh Lin
口試委員:
學位類別: 碩士
Master
系所名稱: 工學院 - 動力機械工程學系
Department of Power Mechanical Engineering
論文出版年: 2006
畢業學年度: 94
語文別: 中文
論文頁數: 98
中文關鍵詞: X射線電腦斷層掃瞄BGA檢測濾波逆投影法
外文關鍵詞: X-ray Computed Tomography (CT), BGA inspection, Filtered Back-Projection (FBP)
相關次數: 點閱:3下載:0
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
  • 電子製造封測業面對未來的無鉛製程以及高密度化的發展趨勢下,傳統二維自動化光學檢測(Automatic Optical Inspection)方式因受限於光源打光角度,攝影取像角度等種種因素,漸漸無法勝任於更高精密度的電子產品檢測。此時,利用X射線進行三維結構的影像重建,最後以所得到的立體影像來檢測出生產線上的製程缺陷,已逐漸獲得業界的重視,極可能在未來在電子產品檢測上扮演極其吃重的角色。
    自從電腦斷層掃瞄發明之後,利用X射線輔以電腦強大的運算能力重建出的斷面影像為近代的醫療做出不小的貢獻。如今我們想要將它應用在製造檢測上面,勢必得對其基本原理與技術作一定程度的探討與研究。本研究使用理論發展較為完備的濾波逆投影法(Filtered Back-Projection)來重建待測影像,並將結果輔以相關係數找出重建三維BGA錫球結構之最佳參數,最後依據所得到的影像與資訊來檢測是否有瑕疵或缺陷出現。


    Electronics manufacturing and IC packaging & testing industries confront the tendencies of higher component density and Pb-free manufacturing process in the future. Traditional two-dimension automatic optical inspection machine is limited by several factors, such as angles of the light source and photographing, it is not able to fulfill the need in the future. Meanwhile, the technique of using x-ray image to reconstruct three-dimensional image to inspect the product gradually grab the attention of the industry. It is believed this approach will play an important role in the near future.
    Since computed tomography (CT) is developed, computer has a powerful arithmetic ability that can reconstruct the section images of structure, which is a great contribution to modern medical science. Nowadays, in order to apply this technique in manufacturing and inspection process, its basic principles and technologies must be carefully studied. In this dissertation, finding the best parameter of filtered back-projection (FBP) method by the correlation coefficient (CC) can rebuild the 3D BGA structure and these images can detect the deficiencies is existed or not.

    摘要 I ABSTRACT II 誌謝 III 目錄 IV 圖目錄 VI 表目錄 IX 第一章 緒論 1 1-1 研究背景 1 1-2 研究動機與目的 3 第二章 文獻回顧 8 2-1 電腦斷層掃瞄的基本原理與方法 9 2-2 X射線的特性 10 2-3 投影技術 13 2-4 影像重建演算法 17 第三章 研究方法與步驟 29 3-1 投影方式 30 3-2 濾波逆投影演算法原理與步驟 33 3-3 實驗參數 37 3-4 標準測試影像與重建影像指標 42 第四章 實驗結果與討論 53 4-1 修正光束硬化之偽影 54 4-2 平行光源模擬重建結果 57 4-3 扇型光源模擬重建結果 62 4-4 重建三維BGA結構 68 第五章 結論與未來展望 91 5-1 結論 91 5-2 未來展望 93 參考文獻 95

    [1] Intel’s 1999 Packaging Databook, Intel Corporation, New York, 2000.
    [2] AMD Functional Data Sheet, 754 Pin Package, Advanced Micro Devices, New York, 2004.
    [3] 宋維泰,「封裝技術探索」,大椽股份有限公司,台北市,2005。.
    [4] 黃顯凱,「無鉛替代焊料之對應製程解決對策剖析」,北京電子工業出版社,北京,2004。
    [5] T.D. Moore, “Three-dimensional x-ray laminography as a tool for detection and characterization of BGA package defects,” IEEE, Transactions on Components and Packaging Technologies, Vol. 25, No. 2, pp. 224-229, June 2002.
    [6] A.C. Kak, and M. Slaney, Principles of Computerized Tomographic Imaging, IEEE Press, New York, 1988.
    [7] S. Krimmel, J. Stephan, and J. Baumann, “3D computed tomography using a microfocus X-ray source: Analysis of artifact formation in the reconstructed images using simulated as well as experimental projection data,” Nuclear Instruments and Methods in Physics Research, Section A-542, pp. 399-407, February 2005.
    [8] G.T. Herman, “Correction for beam hardening in computed tomography,” Physics in Medicine and Biology, Vol. 24, pp. 81-106, 1979.
    [9] P. Hammersberg, and M. Mangard, “Correction for beam hardening artifacts in computerized tomography,” Journal of X-ray Science Technology, Vol. 8, pp. 75-93, 1998.
    [10] F. Jian, and L. Hongnian, “ Beam-hardening correction method based on original sinogram for X-CT,” Elsevier, Nuclear Instruments and Methods in Physics Research, Section A-556, pp. 379–385, 2005.
    [11] S. Gondrom, and M. Maisl, “3D Reconstructions of Micro-System Using X-Ray Tomographic Methods,” The 16th World Conference on Nondestructive Testing, Paper Code 568, Montreal, 2004.
    [12] S.T. Kang, and H.S. Cho, “A projection method for reconstruction X-ray images of arbitrary cross-section,” NDT&E International, Vol. 32, pp. 9-20, 1999.
    [13] V. Sankaran, A.R. Kalukin, and R.P. Kraft, “Improvements to X-ray laminography for automated inspection of solder joints,” IEEE Transactions on Components and Packaging Technologies, Part C, Vol. 21, No. 2, pp. 148-154, 1998.
    [14] S. Hata, and D. Shima, “Relative Stereo Method for 3-D Measurement in Production Lines,” The 9th IEEE International Conference on Emerging Technologies and Factory Automation, Vol. 2, pp. 479-482, Lisbon, 2003.
    [15] J. An, Y.B. Cho, and D.G. Gweon, “A new method for image separation of overlapped images from a two-layered printed circuit board (PCB),” Elsevier, Image and Vision Computing, Vol. 15, pp. 861-866, 1997.
    [16] S. Bord, A. Clement, J.C. Lecomte, and J.C. Marmeggi, “An X-ray tomography facility for I.C. industry at STMicroelectronics Grenoble,” Elsevier, Microelectronic Engineering, Vol. 61–62, pp. 1069-1075, 2002.
    [17] M. Ming, and Z. LI, “Study on limited projections in micro-focus X-Ray swing laminography,” International Conference on Computing in High Energy and Nuclear Physics, Data Handling and Storage 4-006, Beijing, 2001.
    [18] G.T. Herman, Image Reconstruction From Projections: The Fundamentals of Computerized Tomography, Academic Press, New York, 1980.
    [19] A.H. Andersen, and A.C. Kak, “ Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm,” Ultrasonic Imaging, Vol. 6, pp. 81-94, 1984.
    [20] Y.J. Roh, and H.S. Cho, “ A Uniform and Simultaneous Algebraic Reconstruction Technique for X-Ray Digital Tomosynthesis,” Materials Evalution(USA), Vol. 60, No 11, pp. 1350-1357, 2002.
    [21] T. Kohler, R. Proksa, and T. Nielsen,” SNR-Weighted ART Applied to Transmission Tomography,” IEEE Nuclear Science Symposium Conference Record, Vol. 4, pp. 2739-2742, 2004.
    [22] K. Mueller, R. Yagel, and J.J. Wheller, “ Anti-Aliased Three-Dimensional Cone-Beam Reconstruction of Low-Contrast Objects with Algebraic Methods,” IEEE Transactions on Medical Imaging, Vol. 18, No. 6, pp. 519-537, 1999.
    [23] Michael Unser, “ Splines – A Perfect Fit for Signal and Image Processing,” IEEE Signal Processing Magazine, Vol. 16, No. 6, pp. 22-38, 1999.

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE