公开(公告)号：US20200004234A1

公开(公告)日：2020-01-02

申请号：US16538689

申请日：2019-08-12

Applicant: Applied Materials, Inc.

Inventor： Jimmy ISKANDAR ,  Jianping ZOU ,  Parris C.M. HAWKINS ,  James MOYNE

IPC: G05B23/02

Abstract: Described herein are methods, apparatuses, and systems for reducing equipment repair time. In one embodiment, a computer implemented method includes collecting, with a system, data including test substrate data or other metrology data and fault detection data for maintenance recovery of at least one manufacturing tool in a manufacturing facility and determining, with the system, a relationship between tool parameter settings for the at least one manufacturing tool and at least some collected data including the test substrate data. The method further includes utilizing zero or more virtual metrology predictive algorithms and at least some collected data to obtain a metrology prediction and applying multivariate run-to-run (R2R) control modeling to obtain a state estimation including a current operating region of the at least one manufacturing tool based on the test substrate data and obtain at least one tool parameter adjustment for at least one target parameter for the at least one manufacturing tool. Applying multivariate run-to-run (R2R) control modeling to obtain tool parameter adjustments for at least one manufacturing tool occurs after maintenance to reduce maintenance recovery time and to reduce requalification time.

公开(公告)号：US20180217566A1

公开(公告)日：2018-08-02

申请号：US15889906

申请日：2018-02-06

Applicant: Applied Materials, Inc.

Inventor： James MOYNE

IPC: G05B13/02 ,  G05B23/02 ,  G06N5/04

CPC classification number: G05B13/026 ,  G05B23/0297 ,  G05B2219/31459 ,  G05B2219/31465 ,  G05B2219/31483 ,  G06N5/04 ,  Y02P90/86

Abstract: Described herein are methods, apparatuses, and systems for determining adaptive predictive algorithms for virtual metrology. In some embodiments, a computer implemented method identifies a plurality of predictive algorithms. The method determines when to use one or more of the plurality of predictive algorithms to predict one or more virtual metrology variables in a manufacturing facility.