Optical inspection of wafers using large-area defect detection and sampling

Abstract

In the absence of in-line electrical test monitors, semiconductor manufacturers must rely on data from optical inspections to identify and control defects. To be effective, optical inspection must be reduced to terms which have physical significance to the process engineer. The data must be able to show trends over time, distributions of defect types causing the most harm to the product, and net change after elimination of defects. Further, it must be able to predict the health of product with a high degree of consistency. This paper describes how optical defect inspection, using large-area detection and a consistent automatic sampling algorithm, can be used to monitor and control defect levels on product. This method has been a significant contributor to rapid defect learning on the 16-Mb DRAM manufacturing line at IBM.<>