現今的諸多產品在判斷品質的好壞或是製程的狀態可利用監控資料是否滿足某個特定函數或是曲線關係來判定，這一型態的品質資料稱之為輪廓資料。本文利用共同信賴帶和變異數轉換的概念來建構新的管制圖，並用於監控一般線性模型的輪廓資料。我們比較所提出的監控方法與現存監控方法的監控效率，並分別討論在不同製程參數改變狀況下的表現。當管制圖發生了失控警訊後，我們利用最大化一般概似比的方法來估計製程的改變點，接著利用個別的診斷檢定統計量來診斷製程模型中的那些參數發生了改變。當輪廓資料為一般線性模型時，利用共同信賴帶的管制圖，在監控製程的失控與製程改變點的估計或是判斷製程那些參數發生改變的診斷都有不錯的結果。最後我們利用一個例子來說明實際上如何操作及使用本文所提出的監控方法。

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