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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/117441


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    題名: 無母數模糊相關權重指數加權移動平均管制圖設計
    An nonparametric Fuzzy Relative Weight Exponentially Weighted Moving Average control chart design
    作者: 游善涵
    You, Shan Han
    貢獻者: 鄭宇庭
    郭訓志
    Cheng, Yu Ting
    Ku, Hsun Chih
    游善涵
    You, Shan Han
    關鍵詞: 無母數管制圖
    移動加權平均
    模糊相關權重
    日期: 2018
    上傳時間: 2018-06-01 17:34:09 (UTC+8)
    摘要: 隨著品質管制技術的開發，越來越多產業將品質管制的理念應用在產業資料中，而品質管制的方法非常多樣，其中統計製程管制(SPC)為品質管制中重要的技術，其主要是以統計理論背景做支持對產品製程進行監控，本文也將針對SPC中理論背景較完整的管制圖方法做進一步的研究，然而品管在實務應用上，母體資料通常為非特定分配或者未知分配，諸多文獻中已證實，若使用特定假設分配的有母數管制圖用於製程狀態為非假設分布時，會導致管制狀態下的平均連串長度不穩健的情形，若使用無母數管制圖做監控，其管制狀態平均連串長度具有穩健性，因此無母數管制圖實用性能高出許多，近年來對無母數管制圖的研究越來越進步，然而現存的無母數管制圖大多是針對產品製程中平均數、變異數的變動，或者是使用符號函數(sign function)、排序(rank)等方式對觀測值和目標值的差距做監控，又或者觀察資料的分佈狀況監控其分配或目標值是否有偏移的情形等，較少有針對觀測值前後之間變動的差距來偵測資料出現偏移的狀況，因此本文提出一個新的無母數管制圖，想利用模糊相關權重統計量的性質來呈現觀測值之間變動的情形，以此統計量為基礎，建構無母數模糊相關權重指數加權平均(FRWEWMA)管制圖，對製程資料中的平均數(位置參數)和標準差(尺度參數)進行監控，並透過平均連串長度來比較FRWEWMA 管制圖和其他管制圖偵測效能的差異與優勢為何。
    參考文獻: 一、中文文獻
    1. 黃榮臣、張耕銘，2012，利用無母數EWMA 管制圖監控製程平均數/位置參
    數與變異數/尺度參數。
    2. 黃子銘、鄭舜壕，2010，無母數指數加權移動平管制圖伴隨變動管制界線。
    二、英文文獻
    1. Amin, R.W. and A. J. Searcy. 1991. A nonparametric exponentially weighted
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    Computation, Vol. 20, No. 4, pp.1049-1072.
    2. Balakrishnan, N. and H. K.T. Ng. 2006. Precedence-type tests and applications.
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    316.
    4. Chahraborti, S. 2011. Distribution-Free quality control charts.
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    charts: An overview and some results. Journal of Quality Technology, Vol. 33,
    No3, pp.304-315.
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    2561.
    12. Gramham, M. A., S. Chahraborti and S. W. Human. 2011. A nonparametric
    exponentially weighted moving average signed-rank chart for monitoring
    location. Computational Statistics & Data Analysis, Vol. 55, No. 8, pp.2490-
    2503.
    13. Hackl, P. and J. Leodolter. 1999. A control chart based on ranks. Journal of
    Quality Technology, Vol. 23, No. 2, pp.117-124.
    14. Longcheen, H., C. J. Huang and Y. H. T. Wang. 2010. New EWMA control
    charts for monitoring process dispersion. Computational Statistics & Data
    Analysis, Vol. 54, No. 10, pp.2328-2342.
    15. Lucas, M. J. and S. M. Saccucci. 1990. Exponentially weighted moving average
    control schemes: properties and enhancements. Technometrics, Vol. 32, No. 1,
    pp.1-12.
    16. Montgomery, D. C., G. C. Runger and N. F. Hubele. 2009. Statistical quality
    control. pp. 386-411.
    17. Roberts, S. W. 1959. Control chart test based on geometric moving averages.
    Technometrics, Vol. 1, No. 3, pp.239-250.
    18. Robinson, P. B. and T. Y. Ho. 1978. Average run lengths of geometric moving
    average charts by numerical methods. Technometrics, Vol. 20, No. 1, pp.85-93
    19. Stoumbos, Z. G. and J. H. Sullivan. 2002. Robustness to non-normarlity of
    multivariate EWMA control chart. Journal of Quality Technology, Vol. 34, No.
    3, pp.260-276.
    20. Li, S. U., T. L. Ching and S. H. Ng. 2010. Nonparametric CUSUM and EWMA
    control charts for detecting mean shifts. Journal of Quality Technology, Vol. 42,
    No. 2, pp.209-226.
    21. Woodall, W. H. and D. C. Montgomery. 1999. Research issues and ideas in
    statistical process control. Journal of Quality Technology, Vol. 49, No. 4,
    pp.376-386
    描述: 碩士
    國立政治大學
    統計學系
    105354012
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0105354012
    資料類型: thesis
    顯示於類別:[統計學系] 學位論文

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