隨著製程技術日新月異，為了減少外部及內部的失敗成本，品質管理的概念因此逐漸受到重視，品質管理相關理論在這幾十年來逐漸發展成熟。其中統計製程管制(Statistical Process Control, SPC)是一套好用的工具，主要是透過蒐集資料，透過統計分析的方法，對生產過程做即時的監控。管制圖是其中被廣泛應用的工具之ㄧ，傳統的修華特管制圖(Shewhart control chart)適合用在製程一開始時，主要是用來偵測製程過程中有明顯原因的製程變異，將製程帶入穩定狀態，並得到製程中的製程平均數與製程變異數。移除明顯原因的製程變異進入穩定階段後，進行小範圍位移的監測，常用的方法是累積和管制圖(cumulative sum control chart, CUSUM control chart)、指數加權移動平均管制圖(exponentially weighted moving average control chart, EWMA control chart)，CUSUM、EWMA可以針對特定位移去進行參數最佳化的設定，小範圍位移時有不錯的監測效果，但缺點為當實際位移不接 近特定位移時，其監測效果不佳。本研究利用Kullback-Leibler distance(K-L distance)以及最大概似法的概念建構不需要事先設定參數且可以同時監測製程平均數與變異數的管制圖，稱為Information-Theoretical Based Process Control Chart，簡稱為 管制圖，監測能力使用期望警示時間(average time to signal, ATS)當作績效指標。根據模擬結果分析可知在小範圍位移有不錯監測效果，在大範圍位移時監測效果不輸給其他管制圖，整體來說 是一個易於使用且有不錯監測效果的管制圖。

The objective of this study is to construct a new type of control chart based on Kullback-Leibler distance of information theory. We name this control chart Information-Theoretical Based Process Control Chart (IPC( , ) control chart). This study considers detecting the mean shift, variance shift and both shift of a normally distributed process. We use a statistic which is a derivation of Kullback-Leibler distance to construct the IPC( , ) control chart. The control limits of the control chart are obtained by simulation with 100,000 runs when in-control average time to signal is 1481. Using the control limits acquired above, we get the out of control average time to signal for various shift sizes and three shift types. The performance of control charts are measured by average time to signal in this study. The results of IPC( , ) control chart are compared with cumulative sum combination(CUSUM combination), and generalized likelihood ratio (GLR) control chart. The IPC( , ) control chart is effective in detecting shift of small sizes, but less effective in detecting shift of large sizes. The results are close to the CUSUM combination and GLR control charts. It is shown that the overall performance of IPC( , ) control chart is good. An advantage of IPC( , ) control chart is that it does not require users to specify control chart parameters while CUSUM combination control chart have to for detecting a specific mean and variance shift faster.

中文文獻：
李庭媁，應用資訊理論於管制圖之建構，國立成功大學工業與資訊管理研究所碩士論文，民國一百零三年六月。
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