A NEURAL-NETWORK-BASED PROCEDURE FOR THE PROCESS MONITORING OF CLUSTERED DEFECTS IN INTEGRATED-CIRCUIT FABRICATION

In integrated circuit (IC) fabrication, a wafer's defects tend to clus ter. As the wafer size increases, the clustering phenomenon of the def ects becomes increasingly apparent. When the conventional control char t (c chart) is used, the clustered defects frequently cause many false alarms. In this study, we propose a neural network-based procedure fo r the process monitoring of clustered defects in IC fabrication. The p roposed procedure can reduce the phenomenon of the false alarms caused by the clustered defects. A case study is also presented to show the effectiveness of the proposed procedure. (C) 1997 Elsevier Science B.V .