Reducing metrology mean-time-to-detect by utilizing product data

The limitations of existing methodology to maintain metrology fleet matching and stability is being strained by increasingly complex integrations. As the number of measurements also increase within the integration, the ability to quickly detect issues on metrology is critical to prevent product excursions. This paper will review the traditional methodologies for metrology fleet matching and stability and propose a new methodology. A strong emphasis will be placed on using product data to detect tool issues in real time via Pooled and Normalized Product Data Analysis to improve Mean-Time-To-Detect.