一般製造業的品質管理常以管制圖及製程能力分析監控產品及製程的品質，並藉由製程能力指標判斷此製程是否達到產品規格要求的標準。
由於關鍵品質特性大多以計量值(variable data)方式呈現，因此多數學者均致力於計量型製程能力指標之研究。但實務上，仍有不少製程檢驗係以Go/No-Go之方式進行，例如燈罩是否有裂痕、紙張有無汙點等，均屬計數型資料(attribute data)型態，目前已有部分學者如Borges et al.(2001)、Perakis 與Xekalaki(2002)及Hsieh與Tong(2006)等針對此類型之資料制定製程能力指標。但彼等所提出之指標均未考量瑕疵嚴重程度不同其權重應有所區別。因此，本研究係探討考量瑕疵嚴重程度不同時計數型製程能力指標之制定與評估，我們首先針對Perakis與Xekalaki(2002)提出的C_pcu指標進行修正，並據此制定出新的製程能力指標C_D。
接著，以模擬的方式評估比較當瑕疵嚴重程度不同時新指標C_D與Borges et al. (2001)提出的C指標及Perakis 與Xekalaki(2002)的C_pcu指標是否能準確反映製程良率的變化。結果發現無論在參數的敏感度分析或權重改變對於指標的影響分析中，我們所提之新指標C_D均較能穩健地反映良率的變化。此外，我們亦建置製程良率與新指標之對照表，藉此呈現C_D指標隨良率之不同而產生改變之狀況。
最後，我們以長春化工絕緣紙汙點之嚴重程度為例，說明新製程能力指標C_D可正確地反映計數型製程實際改善的成效，研究結果可作為工廠品管單位在評估製程良率表現時之參考。

Statistical control charts and process capability analysis are commonly used to monitor the quality of products through processes in manufacturing industries. Due to the fact that the data for most quality characteristics are collected in variable type, many process capability indices for variable data have been developed in the past decades. However, there are quite a processes in which the data are collected in Go/No-Go or attribute type. For example, the cracks appear on lampshade or the black spots on the insulation paper.
Borges et al.(2001), Perakis and Xekalaki(2002) and other researchers have proposed PCIs for attribute data, such as C and C_pcu indices etc. But, these indices do not take the information of defect severity into account. Therefore, it is necessary to develop a new process capability index for attribute data by taking the consideration of defect severity. Modifying Perakis and Xekalaki(2002)’s C_pcu index, we propose a new process capability index C_D in this research. Then, the simulation method is used to compare the performance of three indices C_D,C and C_(pcu )in terms of properly reflecting the yield change. The simulation results show that our proposed index C_D outperforms C and C_pcu indices during the sensitivity and impact analysis for parameter changes under different weight combinations. We further construct a comparison table to show the process yield changes when the new capability index C_D varies.
Finally, a realistic example of quality improvement for the insulation papers manufactured in Taiwan Chang Chung Company is used to demonstrate that the new process capability index C_D can properly reflect the improvement results. Hopefully, the new index and its practical application can provide a useful reference for quality practitioners in evaluating the process quality for attribute data occurred in industries.

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