管制圖在製造業中，管理流程品質非常重要。管制圖重要性在於能快速指出生產過程中品質是否產生異常。持續監控流程品質變化，能夠確保製造業產品品質穩定。現有管制圖文獻大多假設單變量和多變量製程在統計管制下，數據呈現連續性。

本研究中，首先我們建立具有特定用途的 EWMA 多項式比例管制圖。我們使用兩 階段檢測方式來處理此問題:考慮 3 個比例下( p1, p2, p3 )，如果 p1 或 p2 發生變化，但 p1 和 p2 的總和維持不變，則組合後的管制圖不會顯示變化。模擬結果說明，我們的 p1 管制 圖可以快速檢測 p1 變化，並提供變化量 delta 大小。其次，我們探討從二元常態分配轉換到多項式分配，藉由每個品質變數規格界線，進而分類不同類型不良品比例。

Control charts are important in managing process quality in manufacturing.They are important because they can quickly indicate any changes in the quality of a production process. This constant monitoring of changes in process quality is essential for ensuring consistent and high-quality products in manufacturing. Much of the existing literature on control charts assumes that the data distribution follows a continuous pattern when both univariate and multivariate processes are in control.

In this research, firstly, we construct specified EWMA multinomial p charts that have particular uses. We utilize two-stage detection to approach the problem: consider triple proportions, ( p1, p2, p3 ), if p1 or p2 changes but the total of p1 and p2 stays the same, the combined chart doesn't show the change. The simulations suggest that our p1 chart can quickly detect changes in p1 and measure the magnitude of the change in delta. Secondly, we transform bivariate normal distribution to multinomial distribution and classify proportions by specification limits.

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