公开(公告)号：US20210397172A1

公开(公告)日：2021-12-23

申请号：US17296316

申请日：2019-10-30

Applicant: ASML NETHERLANDS B.V.

Inventor： Abraham SLACHTER ,  Wim Tjibbo TEL ,  Daan Maurits SLOTBOOM ,  Vadim Yourievich TIMOSHKOV ,  Koen Wilhelmus Cornelis Adrianus VAN DER STRATEN ,  Boris MENCHTCHIKOV ,  Simon Philip Spencer HASTINGS ,  Cyrus Emil TABERY ,  Maxime Philippe Frederic GENIN ,  Youping ZHANG ,  Yi ZOU ,  Chenxi LIN ,  Yana CHENG

IPC: G05B19/418

Abstract: A method for analyzing a process, the method including obtaining a multi-dimensional probability density function representing an expected distribution of values for a plurality of process parameters; obtaining a performance function relating values of the process parameters to a performance metric of the process; and using the performance function to map the probability density function to a performance probability function having the process parameters as arguments.

公开(公告)号：US20200050099A1

公开(公告)日：2020-02-13

申请号：US16606791

申请日：2018-05-04

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi ZOU ,  Chenxi LIN ,  Yu CAO ,  Yen-Wen LU ,  Been-Der CHEN ,  Quan ZHANG ,  Stanislas Hugo Louis BARON ,  Ya LUO

IPC: G03F1/36 ,  G06F17/50 ,  G06N20/10 ,  G05B19/4097 ,  G06K9/46 ,  G06T7/60 ,  G06T7/00

Abstract: A method including: obtaining a portion of a design layout; determining characteristics of assist features based on the portion or characteristics of the portion; and training a machine learning model using training data including a sample whose feature vector includes the characteristics of the portion and whose label includes the characteristics of the assist features. The machine learning model may be used to determine characteristics of assist features of any portion of a design layout, even if that portion is not part of the training data.

公开(公告)号：US20190147127A1

公开(公告)日：2019-05-16

申请号：US16300380

申请日：2017-04-20

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi ZOU ,  Chenxi LIN ,  Stefan HUNSCHE ,  Marinus JOCHEMSEN ,  Yen-Wen LU ,  Lin Lee CHEONG

IPC: G06F17/50 ,  G03F7/20 ,  G06N20/00 ,  G06T7/00

Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.