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公开(公告)号:US20240153062A1
公开(公告)日:2024-05-09
申请号:US18406485
申请日:2024-01-08
Applicant: Micron Technology, Inc.
Inventor: Amitava Majumdar , Qianlan Liu , Pradeep Ramachandran , Shawn D. Lyonsmith , Steve K. McCandless , Ted L. Taylor , Ahmed N. Noemaun , Gordon A. Haller
CPC classification number: G06T7/0004 , G01B1/00 , G01B11/00 , G01N21/211 , G01N21/4738 , G06F30/367 , G06N20/00 , G01B2210/56 , G06T2207/10024 , G06T2207/10152 , G06T2207/20081 , G06T2207/30148
Abstract: A method of predicting virtual metrology data for a wafer lot that includes receiving first image data from an imager system, the first image data relating to at least one first wafer lot, receiving measured metrology data from metrology equipment relating to the at least one first wafer lot, applying one or more machine learning techniques to the first image data and the measured metrology data to generate at least one predictive model for predicting at least one of virtual metrology data or virtual cell metrics data of wafer lots, and utilizing the at least one generated predictive model to generate at least one of first virtual metrology data or first virtual cell metrics data for the first wafer lot.
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公开(公告)号:US11869178B2
公开(公告)日:2024-01-09
申请号:US17117222
申请日:2020-12-10
Applicant: Micron Technology, Inc.
Inventor: Amitava Majumdar , Qianlan Liu , Pradeep Ramachandran , Shawn D. Lyonsmith , Steve K. McCandless , Ted L. Taylor , Ahmed N. Noemaun , Gordon A. Haller
CPC classification number: G06T7/0004 , G01B1/00 , G01N21/211 , G01N21/4738 , G06F30/367 , G06N20/00 , G01B2210/56 , G06T2207/10024 , G06T2207/10152 , G06T2207/20081 , G06T2207/30148
Abstract: A method of predicting virtual metrology data for a wafer lot that includes receiving first image data from an imager system, the first image data relating to at least one first wafer lot, receiving measured metrology data from metrology equipment relating to the at least one first wafer lot, applying one or more machine learning techniques to the first image data and the measured metrology data to generate at least one predictive model for predicting at least one of virtual metrology data or virtual cell metrics data of wafer lots, and utilizing the at least one generated predictive model to generate at least one of first virtual metrology data or first virtual cell metrics data for the first wafer lot.
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公开(公告)号:US20200051235A1
公开(公告)日:2020-02-13
申请号:US16100729
申请日:2018-08-10
Applicant: Micron Technology, Inc.
Inventor: Amitava Majumdar , Qianlan Liu , Pradeep Ramachandran , Shawn D. Lyonsmith , Steve K. McCandless , Ted L. Taylor , Ahmed N. Noemaun , Gordon A. Haller
Abstract: A method of predicting virtual metrology data for a wafer lot that includes receiving first image data from an imager system, the first image data relating to at least one first wafer lot, receiving measured metrology data from metrology equipment relating to the at least one first wafer lot, applying one or more machine learning techniques to the first image data and the measured metrology data to generate at least one predictive model for predicting at least one of virtual metrology data or virtual cell metrics data of wafer lots, and utilizing the at least one generated predictive model to generate at least one of first virtual metrology data or first virtual cell metrics data for the first wafer lot.
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公开(公告)号:US20210090246A1
公开(公告)日:2021-03-25
申请号:US17117222
申请日:2020-12-10
Applicant: Micron Technology, Inc.
Inventor: Amitava Majumdar , Qianlan Liu , Pradeep Ramachandran , Shawn D. Lyonsmith , Steve K. McCandless , Ted L. Taylor , Ahmed N. Noemaun , Gordon A. Haller
Abstract: A method of predicting virtual metrology data for a wafer lot that includes receiving first image data from an imager system, the first image data relating to at least one first wafer lot, receiving measured metrology data from metrology equipment relating to the at least one first wafer lot, applying one or more machine learning techniques to the first image data and the measured metrology data to generate at least one predictive model for predicting at least one of virtual metrology data or virtual cell metrics data of wafer lots, and utilizing the at least one generated predictive model to generate at least one of first virtual metrology data or first virtual cell metrics data for the first wafer lot.
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