A Comprehensive "Big-Data-Based" Monitoring System for Yield Enhancement in Semiconductor Manufacturing

In this work, we focus on yield analysis task where engineers identify the cause of failure from wafer failure map patterns and manufacturing histories. We organize yield analysis task into 3 stages, failure map pattern monitoring. failure cause identification and failure recurrence monitoring, and incorporate machine learning and data mining technologies into each stage to support engineers' work. The important point is that big data analysis enables comprehensive and long-term monitoring automation. Machine learning and data mining techniques are integrated into a real automated monitoring system with interfaces familiar to engineers to attain large yield enhancement.