Defect cluster analysis to detect equipment-specific yield loss based on yield-to-area calculations

摘要

Defect parameter extraction plays an important role in process control and yield prediction. A methodology of evaluating wafer level defect clustering will be presented to detect equipment specific particle contamination. For that, imaginary wafermaps of a variety of different chip areas are generated to calculate a yield-to-area dependency. Based on these calculations a Micro Density Distribution (MDD) will be determined for each wafer. The range and course of the MDD may indicate specific failures of equipment tools.