In the modeling and control of semiconductor manufacturing, the control engineer must be aware of all influences on the performance of each process. Upstream processes may affect the wafer substrate in a manner that alters performance in downstream operations, and the context within which a process is run may fundamentally change the way the process behaves. Incorporating these influences into a control method ultimately leads to better predictability and improved control performance. Control threads are a way of incorporating these effects into the control of a process by partitioning historical data into groups within which the deterministic sources of variation are uniform. However, if there are many products, which require many threads to be defined, there may be insufficient data to model each thread. This multi-product-multi-tool manufacturing environment ("high-mix") requires advanced methodologies based on state estimation and recursive least squares. Several such approaches are compared in this paper based on simulation models for a high-mix fab.
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