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Big data analytics to improve photomask manufacturing productivity

Driven by Moore's law, the number of transistors fabricated on a wafer will be doubled every 12 or 24 months with a lower average selling price [1]. When IC production enters into the nanometer generation, many factors including recipe, process, tool, and chamber with the multi-collinearity affect the yield that are hard to detect and interpret. This paper describes both our practice on big data analytics to a real-time remote monitor mask production line, and how to monitor critical production machines' parameters, and then setup an alert mechanism, all of which are helpful in improving production machine usage and production line productivity, and decreasing mask scrap.