Controlling etch tools using real-time fault detection and classification

摘要

Semiconductor manufacturers use process control methods and an analysis of tool sensor outputs to improve yields, increase tool productivity, and reduce manufacturing costs. Statistical process control (SPC) utilizes statistical algorithms to detect excursions. In contrast, this article presents a novel fault detection and classification (FDC) approach from Straatum (Dublin, Ireland) that is based on a pattern-recognition algorithm. Outputting a chamber-status metric known as the plasma index, this real-time FDC method is in place at ProMOS Technologies (Hsinchu, Taiwan), a 200-mm manufacturing facility that runs a variety of semiconductor tools. Based on a number of case studies, this article discusses the use of Straatum's FDC method in conjunction with several DRM oxide etch tools from Tokyo Electron (Tokyo).