English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 73279/105095 (70%)
造訪人次 : 19273750      線上人數 : 43
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/106396
    請使用永久網址來引用或連結此文件: http://nccur.lib.nccu.edu.tw/handle/140.119/106396


    題名: IC基板製程時間之特徵選擇研究-以鑽孔作業為例
    A Study of Features Selection to Process Time of IC Substrate - For Example of Drilling Operation
    作者: 宋伯謙
    Soong, Elias
    貢獻者: 劉文卿
    許志堅

    宋伯謙
    Elias Soong
    關鍵詞: 特徵選擇
    產品特徵
    製程時間
    資料挖礦
    Features Selection
    Product Characteristics
    Process Time
    Data-mining
    日期: 2017
    上傳時間: 2017-02-08 16:34:37 (UTC+8)
    摘要: 在數據分析的領域中,尤其在大數據的領域之中,因常含有相當高維度的預測變數,故特徵選擇是一個很重要的主題。這個主題在半導體的應用上,已經獲得相當豐碩的成果,但在IC基板的應用上,成果就相對顯得貧乏。所以,此次的研究(以IC基板中鑽孔製程為例)將透過以下的試驗方法(含:GR-SNBC (Gain Ratio with Naive Bayes Classifier)、SU-SNBC (Symmetrical Uncer-tainty with Naive Bayes Classifier)與SU-CART (Symmetrical Uncer-tainty with Classification and Regression Tree Classifier)),來建立可應用於IC基板製程時間預測上的一組屬性。最後,此一研究的成果不僅在於,使用資料挖礦的方法,來找出一組具有顯著性,而且可以用來預測的IC基板製程時間的產品特徵屬性;而且,發現若為了縮短製程時間,來自產品結構本身的因子,會比來自產品在生產管理上的因子更具顯著的效果。
    Feature selection is significate subject in domain of data analysis, especially in big-data with a lot of high dimension predictive variables. In semi-conductor field, this subject has already gotten a plenty of achievement, but not in IC-substrate; so in this research for example of drilling operation, through experiments, it builds a group of se-lective features for this field to predict process time, and the methods used are GR-SNBC (Gain Ratio with Naive Bayes Classifier), SU-SNBC (Symmetrical Uncertainty with Naive Bayes Classifier) and SU-CART (Symmetrical Uncertainty with Classification and Regression Tree Classifier). The contributions of this research are not only a selective product characteristics subset suggested to predict process-time in IC-substrate fab via the data-mining methods here, but also an observation that in order to shorten the process time, the factors of product construction weighs more than production management.
    參考文獻: [1] Backus, P.; Janakiram, M.; Mowzoon, S.; Runger, G.C.; Bhargava, A. "Factory cycle-time prediction with a data-mining ap-proach", Semiconductor Manufacturing, IEEE Transactions on, On page(s): 252 - 258 Volume: 19, Issue: 2, May 2006
    [2] I. Tirkel, "Cycle time prediction in wafer fabrication line by ap-plying data mining methods", Proc. 22nd IEEE/SEMIASMC, pp. 1-5, 2011
    [3] Y. Meidan , B. Lerner , G. Rabinowitz and M. Hassoun, "Cycle-time key factor identification and prediction in semiconductor manufacturing using machine learning and data mining", IEEE Trans. Semicond. Manuf., vol. 24, no. 2, pp. 237-248, 2011
    [4] Chien, C. F., Hsiao, C. W., Meng, C., Hong, K. D., Wang, S. T., 2005. Cycle time prediction and control based on production line status and manufacturing data mining, Proceedings of Inter-national Symposium on Semiconductor Manufacturing Con-ference 2005, 13-15 September, San Jose, California, USA, pp.327-330.
    [5] Hassoun, M. "On Improving the Predictability of Cycle Time in an NVM Fab by Correct Segmentation of the Pro-cess", Semiconductor Manufacturing, IEEE Transactions on, On page(s): 613 - 618 Volume: 26, Issue: 4, Nov. 2013
    [6] Dash, M., & Liu, H. (1997). Feature selection for classifica-tion. Intelligent Data Analysis, 1(1-4), 131-156.
    [7] Liu, H., & Motoda, H. (1998). Feature extraction, construction and selection: A data mining perspective. Norwell,MA: Kluwer Academic Publishers.
    [8] Liu, H., & Motoda, H. (1998). Feature selection for knowledge discovery and data mining. Norwell, MA: Kluwer Academic Publishers.
    [9] A. Whitney, "A direct method of nonparametric measurement selection", IEEE Transactions on Computers, vol. 20, pp.1100-1103, 1971
    [10] S.-H. Chung and H.-W. Huang, "Cycle time estimation for wafer fab with engineering lots", IIE Trans., vol. 34, pp. 105-118, 2002
    描述: 碩士
    國立政治大學
    資訊管理學系
    103356043
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0103356043
    資料類型: thesis
    顯示於類別:[資訊管理學系] 學位論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    604301.pdf3576KbAdobe PDF131檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋