運用統計方法對積體電路製造的晶圓良率做預測與資料探勘

Abstract

積體電路製造中無法控制的因子會造成晶圓良率的變異。此篇論文包含兩個部分，第一個部分探討良率的估計與從晶圓儲藏庫取出多少片晶圓生產才能達成客戶訂單需求的問題。我們運用統計方法來偵測離群值，從歷史資料中選取出學習訓練集，以重複抽樣方法做估計，使用實際的晶圓良率資料做比較分析。第二個部分則是針對找出造成良率下降的故障機台和機台故障時間的問題，使用統計方法來偵測離群值、分群、分類，並使用了實際資料與模擬資料來分析與評估，同時討論了以混合的高斯分配為模型的情形。

The uncontrolled factors in manufacturing cause variations in the yields of wafers in the IC industry. This thesis contains two sections. In the first part, we discuss the problem of yield forecast and decide the number of wafers to be picked from the wafer bank to meet the order of a customer. For this problem, we study the statistical methods of outlier detection, selection of training sets from historical data, and resampling methods. Empirical studies based on the production data in one IC company are conducted to evaluate the performance. In the second part, we aim to find the malfunction equipments and time periods during the manufacturing process that result in low yields at the end. We investigate the statistical methods of outlier detection, clustering analysis, and classification techniques for this problem. Empirical and simulation studies are used to evaluate the performance. Gaussian mixtures are also discussed and studied as well.