- Patent Title: Machine learning systems for monitoring of semiconductor processing
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Application No.: US16297517Application Date: 2019-03-08
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Publication No.: US10795346B2Publication Date: 2020-10-06
- Inventor: Graham Yennie , Benjamin Cherian
- Applicant: Graham Yennie , Benjamin Cherian
- Applicant Address: US CA Santa Clara
- Assignee: Applied Materials, Inc.
- Current Assignee: Applied Materials, Inc.
- Current Assignee Address: US CA Santa Clara
- Agency: Fish & Richardson P.C.
- Main IPC: H01L21/306
- IPC: H01L21/306 ; G05B19/418 ; G05B13/02 ; G06N3/08 ; H01L21/67 ; H01L21/66 ; B24B37/013 ; G06N3/04

Abstract:
Operating a substrate processing system includes receiving a plurality of sets of training data, storing a plurality of machine learning models, storing a plurality of physical process models, receiving a selection of a machine learning model from the plurality of machine learning models and a selection of a physical process model from the plurality of physical process models, generating an implemented machine learning model according to the selected machine learning model, calculating a characterizing value for each training spectrum in each set of training data thereby generating a plurality of training characterizing values with each training characterizing value associated with one of the plurality of training spectra, training the implemented machine learning model using the plurality of training characterizing values and plurality of training spectra to generate a trained machine learning model, and passing the trained machine learning model to a control system of the substrate processing system.
Public/Granted literature
- US20190286075A1 Machine Learning Systems for Monitoring of Semiconductor Processing Public/Granted day:2019-09-19
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