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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/53393


    Title: 多階製程下動態EWMA管制圖之研究(II)
    Other Titles: The Study of Adaptive Ewma Control Charts under Multiple Dependent Process Steps
    Authors: 楊素芬
    Contributors: 國立政治大學統計學系
    行政院國家科學委員會
    Keywords: 數學;多階製程;動態EWMA管制圖
    Dependent process steps, adaptive control scheme, Markov chain, small shift inmean and variance
    Date: 2008
    Issue Date: 2012-08-30 09:59:04 (UTC+8)
    Abstract: 製程管制的目的在能快速診斷出製程上平均數 和/或變異數之異常。唯隨著 生產型態的改變，傳統的舒華特管製圖並不一定都具高度偵測出製程失控的能 力，是以設計符合各種生產型態及能快速診斷出製程發生變異的適當管制技術是 迫切必要的。 本計畫(96.8~99.7)為三年期計畫，將延續我們這幾年之研究；探討多階段相依 製程下(1)以EWMA 管製圖偵測製程平均值發生小偏移的適應性管制技術，(2)以 EWMS 管製圖偵測製程變異數發生小偏移的適應性管制技術，(3)推廣(1)和(2)的結 果，以EWMA and EWMS (暫定)兩個管製圖(或發展出一個EWMA 管製圖)同時偵測製 程平均值和變異數發生小偏移的適應性管制技術，和(4)對(1)~(3) 推廣以經濟統計 觀點設計之。這些研究目前皆尚未有文獻探討，是以這些管制技術的探討不僅在學 術上是值得的且研究結果除具有學術參考價值外，在實務應用上相信對高科技公司 或精密工業之品質提升更是重要，這些方法也可應用於服務業上。 這幾年我們分別探討不少單一製程及相依製程之統計管制方法和經濟統計管制 方法，但這些製程管制方法都只是探討製程平均值及變異數發生大偏移的情形。實 務上，製程平均值 及/或 變異數發生小偏移的情形對大多高科技公司或精密工業更 是普遍。近二十年來，有不少文獻探討單一製程之EWMA 或CUSUM 管製圖以偵測製程 平均值發生小偏移的情形。另有極少數文章提出對EWMA 或CUSUM 管製圖做修飾以偵 測製程變異數發生小偏移的情形。另外，也有一些文章提出適應性管制技術(adaptive control scheme) EWMA 或CUSUM 管製圖以更有效管制製程平均值發生小偏移的情 形。然而這些探討都只限於偵測單一製程平均值或變異數發生小偏移的情形。本研 究將推廣為多階段相依製程的情形並以Markov chain 方法和機率方法分別推導製程 模式，經濟模式和推導計算管製圖的績效模式。 最後，倘若時間允許，我?將進一步探討對計量值(variables)少量多樣(short production runs)的單一生產製程如何建立適應性管制技術的EWMA and/or EWMS 管 製圖以有效管制及偵測出不同規格產品的製程平均值發生小偏移的情形。少量多樣 產品是目前與未來之生產趨勢，傳統之Shewhart 管製圖並不適用於製程管制，而少 量多樣生產之製程管制方法文獻上探討的頗少，且僅限於固定管制技術。有關少量 多樣生產的適應性管制技術目前則尚未有文獻探討，是以是非常值得研究的。 這些研究成果無論在學術上或實務上也都是有參考價值的。
    In the recent years, we have some studies about statistical process control and economic process control for mean and/or variance on a single process or multiple dependent process steps. However, all these studies discuss large shift in mean and/or variance. For advanced technology, discussing the small shift in mean and/or variance is more important and useful. In this NSC project (96.8~99.7), we will study (1) the adaptive control scheme for EWMA charts to monitor process mean on multiple process steps (2) the adaptive control scheme for EWMS charts to monitor process variance on multiple process steps (3) the adaptive control scheme for EWMA and EWMS charts to monitor process mean and variance on multiple process steps (4) extend the results in (1)~(3) to economic statistical design. So far, the topics have not been addressed. The Markov chain approach, probability theory will be used to derive the processes models, processes cost model and AATS (adjusted average time to signal). The performance for these control charts will be measured by comparing with fixed control scheme EWMA and/or EWMS charts, and Shewahrt control charts through numerical analysis. The proposed approaches may also be applied to improve the industrial process or service industry. We expect the results will be more useful and powerful in reality and academic research. If time is available, we will propose adaptive control scheme EWMA chart to detect small shift in process mean for short production runs. The Shewhart charts may not appropriate for short production runs, and this topic has not be addressed so far.
    Relation: 應用研究
    學術補助
    研究期間:9708~ 9807
    研究經費:688仟元
    Data Type: report
    Appears in Collections:[統計學系] 國科會研究計畫

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