一個針對離子植入機之錯誤檢測與錯誤判別的方法

Abstract

在本論文中，我們提出一針對半導體IC製造之離子植入機台Eaton NV6200錯誤檢測與錯誤判別之技術。我們先是就離子植入機與製程中所量測的資料參數加以了解。在錯誤檢測方面，先以Chebyshev Inequality建立出模型的架構，之後再使用模糊分類器建立出錯誤檢測之模型。再以訓練資料及測試資料來模擬驗證此系統之可行性。在錯誤判別方面，亦是使用模糊分類器來建立出錯誤判別之模型。再製作錯誤之資料來模擬驗證此系統之可行性。

In this thesis, we present a fault detection and fault identification technique for Ion-implanter Eaton NV6200 in semiconductor IC fabrication. We first review the Ion-implanter and its relation with the measurement data. Then in fault detection, we use Chebyshev Inequality to build the architecture of our model and use fuzzy classifier to build this model according to the architecture. The usefulness of such an approach is verified by simulations. Then in fault Identification, we also use fuzzy classifier to build the model of fault detection. The usefulness of such an approach is verified by simulations.