Detection of faulty semiconductor wafers using dynamic growing self organizing map

Abstract

Solving product yield and quality problems in a manufacturing process is becoming increasingly more difficult. There are various types of failures and their causes have complex multi-factor interrelationships. Semiconductor manufacturing is very complex due to the large number of processes, diverse equipment set and nonlinear process flows. Its manufacturing database comprises of hundreds of process control, process step and wafer probe data. This huge volume of data coupled with quicker time to market expectations is making finding and resolving problems quickly an overwhelming task. In this study, a methodology developed using dynamic growing self-organizing map (GSOM) to detect the faulty..