統計製程管制(statistical process control)一直是工業界提升產品品質的重要工具。目前單變量管制圖以指數加權移動平均(EWMA)管制圖表現最好，尤其在偏移量小的時候。但這些傳統管制圖只能針對製程中的單一個品質特性作個別監控，無法同時對數個品質特性作監控。然而現今高科技時代來臨，製程的複雜度也日漸提升，品質特性變數也越來越多，因此如何對數個品質特性同時監控，目前有相當多學者利用單變量管制圖的觀念，衍生出不同的多變量管制圖。其中以 Hotelling's T2、MCUSUM、MEWMA最常被討論，又以MEWMA的偵測表現最好。在陳俊宇(2013)碩士論文中提出逐次檢測的概念，並指出在偏移量小時，偵測效率優於EWMA。本論文將此方法推廣到多維度，透過模擬的方式及比較後，得到了同樣的結論，在偏移量小時，偵測效率優於MEWMA。

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