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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Format | Patent |
Language | Chinese English |
Published |
02.12.2022
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Abstract | 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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AbstractList | 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 |
Author | YOGOV SHAY COHEN, ODED BRANOWICZ, BAREK TAL, NOAM STREICH, BOAZ YAACOBI RAHN |
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DocumentTitleAlternate | 用于基于光谱的计量和过程控制的机器和深度学习方法 |
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Snippet | Systems and methods for advanced process control (APC) in semiconductor manufacturing include, for each wafer station of a plurality of wafer stations,... |
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SubjectTerms | BASIC ELECTRIC ELEMENTS ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR ELECTRICITY INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING MEASURING ANGLES MEASURING AREAS MEASURING IRREGULARITIES OF SURFACES OR CONTOURS MEASURING LENGTH, THICKNESS OR SIMILAR LINEARDIMENSIONS PHYSICS SEMICONDUCTOR DEVICES TESTING |
Title | Machine and deep learning method for spectrum-based metrology and process control |
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