关键词: 半导体制造, 晶圆缺陷, 流形调节, 混合模型, 模式识别, 故障诊断

Abstract: To recognize the wafer defects of semiconductor wafer manufacturing process for finding the root causes of out-of-control process,a detecting system for wafer defects recognition was developed.The hierarchical clustering method was applied to group the local defects into clusters,and the number of clusters was determined by silhouette coefficient.To best describe three common defect patterns of wafer (linear,curvilinear,ellipse),Gaussian Mixture Model with Local Consistency(LCGMM) was proposed with respect to the data's distribution on a submanifold of ambient space.Combined with Principal Curve (PC) model,the local defect patterns could be well modeled.On this basis,a hybrid model by integrating LCGMM and PC was constructed,which not only detected more wafer defect patterns but increased the accuracy of recognition rate.The proposed system was applied to real-world and simulate cases,and the effectiveness was proved.

Key words: semiconductor manufacturing, wafer defect, manifold regulation, hybrid models, pattern recognition, fault diagnosis