关键词: 半导体制造, 晶圆缺陷, 模式识别, 隐马尔科夫模型

Abstract: Wafer defect patterns usually indicate the abnormal sources existing in the manufacturing process. Therefore wafer defect recognition plays a crucial important role in finding the root causes of the out-of-control process. This paper develops a model for wafer defect detection and self-adaption recognition. First of all, feature extraction is applied to different wafer patterns. Then based on modeling the various defect patterns with corresponding Hidden Markov Model（HMM）, a dynamic ensemble scheme HMMs is proposed to detect and recognize defect patterns occurring in wafers. The proposed model is successfully applied to WM-811K wafer bin map database and the experimental results prove the effectiveness of the model.

Key words: semiconductor manufacturing, wafer defect, pattern recognition, hidden Markov model