Real-time fault detection and classification for manufacturing etch tools

Abstract

Process control in semiconductor manufacturing has sought to improve yield, increase tool productivity and reduce manufacturing costs through the analysis of tool sensor outputs. Statistical process control (SPC) utilizes statistical algorithms to detect excursion events, but here a novel fault detection and classification (FDC) approach based upon a pattern recognition algorithm is presented. This FDC method from Straatum/spl trade/ is real-time, outputting a chamber status metric known as the plasma index. The system is in place at ProMOS Technologies Inc, 200 mm manufacturing facility on various semiconductor tools - this document presents its implementation on a number of Tokyo/spl trade/ DRM/spl trade/ oxide etch tools and includes a number of case studies.