Machine and deep learning method for spectrum-based metrology and process control
Systems and methods for advanced process control (APC) in semiconductor manufacturing include, for each wafer station of a plurality of wafer stations, receiving a pre-processing set of scatterometry training data measured prior to performing a processing step, receiving a respective post-processing...
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Main Authors | , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
02.12.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Systems and methods for advanced process control (APC) in semiconductor manufacturing include, for each wafer station of a plurality of wafer stations, receiving a pre-processing set of scatterometry training data measured prior to performing a processing step, receiving a respective post-processing set of scatterometry training data measured after performing the processing step, and transmitting the received pre-processing set to the plurality of wafer stations. And receiving a set of process control knob training data indicative of process control knob settings applied during implementation of the processing step; and generating a machine learning model that associates the pre-processed set of scatterometry training data with the changes in the corresponding process control knob training data and the corresponding post-processed set of scatterometry training data to train the machine learning model to recommend changes to the process control knob settings, changes in the pre-processed scatterometry data are |
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Bibliography: | Application Number: CN202180029438 |