應用灰色預測於自我相關製程之品質監控

Using Gray Forecasting Method to Monitor the Autocorrelation Process

陳志堅(Chih-Chien Chen) ； 徐振凱(Chen-Kai Hsu) ； 鄭儀誠(Yi-Cheng Cheng) ； 許銘修(Ming-Hsiu Hsu)

《聯大學報》 5卷2期_下 (2008/12) Pp. 101-115

https://doi.org/10.29847/JNUU.200812.0020

摘要

工業界為了生產高品質的產品，往往會利用管制圖作製程的監控與管制。傳統的管制圖應用的前提為：製程數據必需獨立、無自我相關，然而很多機台設備端、廠務端，甚至化工廠等連續性製程，大都具有自我相關的特性，因此很多傳統的管制圖便顯得不適用。雖然，也有學者提出可以利用時間序列模式等方法來解決自我相關製程之監控問題，然而，建模複雜及應用不易是其最大的問題點。本研究利用灰色預測理論之簡單使用、不需決定任何模式之特性，構建以灰色預測為基礎的殘差管制圖來解決自我相關特性製程的監控問題，同時亦可解決管制參數之間相關性異常的問題。本研究最後以模擬分析及真空設備系統之實例驗證說明此一監控策略的有效性。

關鍵字

自我相關 ； 時間序列 ； 灰色預測 ； 殘差管制圖

並列摘要

The control chart is used to monitor and control industry process for producing high quality products. The process data to be controlled by traditional chart is required to be independent over time and no autocorrelation is involved. However, many process data from equipment parameters or even chemical processes usually violate such assumption and no longer to be suitable by applying the traditional control chart. Although some methods, such as time series model based residual control chart, have been used for solving the autocorrelation data issue, they are too complex to be practiced in industry. In this study, we proposed a Gray forecasting based residual control chart to control the process with the characteristic of autocorrelation. It also can be used to detect the abnormal situation which several variables' correlations have changed. Finally the proposed method is validated by simulation examples and one vacuum system example of real case.

並列關鍵字

autocorrelation ； time series ； Gray forecasting ； residual control chart

參考文獻

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