公开(公告)号：US20210150115A1

公开(公告)日：2021-05-20

申请号：US16629633

申请日：2018-06-20

Applicant: ASML NETHERLANDS B.V.

Inventor： Lin Lee CHEONG ,  Bruno LA FONTAINE ,  Marc Jurian KEA ,  Yasri YUDHISTIRA ,  Maxime Philippe Frederic GENIN

IPC: G06F30/398 ,  G06F30/392

Abstract: A method including obtaining verified values of a characteristic of a plurality of patterns on a substrate produced by a device manufacturing process; obtaining computed values of the characteristic using a non-probabilistic model; obtaining values of a residue of the non-probabilistic model based on the verified values and the computed values; and obtaining an attribute of a distribution of the residue based on the values of the residue. Also disclosed herein are methods of computing a probability of defects on a substrate produced by the device manufacturing process, and of obtaining an attribute of a distribution of the residue of a non-probabilistic model.

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.