- Patent Title: Machine learning systems for monitoring of semiconductor processing
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Application No.: US16297523Application Date: 2019-03-08
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Publication No.: US10969773B2Publication Date: 2021-04-06
- Inventor: Graham Yennie , Benjamin Cherian
- Applicant: Applied Materials, Inc.
- 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: G05B19/418
- IPC: G05B19/418 ; G05B13/02 ; G06N3/08 ; H01L21/306 ; H01L21/67 ; H01L21/66 ; B24B37/013 ; G06N3/04

Abstract:
A method of operating a polishing system includes training a plurality of models using a machine learning algorithm to generate a plurality of trained models, each trained model configured to determine a characteristic value of a layer of a substrate based on a monitoring signal from an in-situ monitoring system of a semiconductor processing system, storing the plurality of trained models, receiving data indicating a characteristic of a substrate to be processed, selecting one of the plurality of trained models based on the data, and passing the selected trained model to the processing system.
Public/Granted literature
- US20190286111A1 Machine Learning Systems for Monitoring of Semiconductor Processing Public/Granted day:2019-09-19
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