公开(公告)号：US20240028910A1

公开(公告)日：2024-01-25

申请号：US18171550

申请日：2023-02-20

Applicant: Samsung Electronics Co., Ltd.

Inventor： Yunjun Nam ,  Bogyeong Kang ,  Hyowon Moon ,  Byungseon Choi ,  Jaemyung Choe ,  Hyunjae Jang ,  In Huh

IPC: G06N3/10 ,  G06N3/08 ,  G06F30/3308

CPC classification number: G06N3/10 ,  G06N3/08 ,  G06F30/3308

Abstract: In a modeling method of a neural network, a first regression model is trained based on first sample data and first simulation result data. The first regression model is used to predict the first simulation result data from the first sample data. The first sample data represent at least one of conditions of a manufacturing process of a semiconductor device and characteristics of the semiconductor device. The first simulation result data are obtained by performing a simulation on the first sample data. In response to a consistency of the first regression model being lower than a target consistency, the first regression model is re-trained based on second sample data different from the first sample data. The second sample data are associated with a consistency reduction factor of the first regression model that is responsible for a prediction failure of the first regression model.

公开(公告)号：US20210056425A1

公开(公告)日：2021-02-25

申请号：US16910908

申请日：2020-06-24

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Changwook JEONG ,  Sanghoon Myung ,  In Huh ,  Hyeonkyun Noh ,  Minchul Park ,  Hyunjae Jang

IPC: G06N3/08 ,  G06N20/00 ,  G06K9/62

Abstract: A method for a hybrid model that includes a machine learning model and a rule-based model, includes obtaining a first output from the rule-based model by providing a first input to the rule-based model, and obtaining a second output from the machine learning model by providing the first input, a second input, and the obtained first output to the machine learning model. The method further includes training the machine learning model, based on errors of the obtained second output.

公开(公告)号：US10650910B2

公开(公告)日：2020-05-12

申请号：US16249543

申请日：2019-01-16

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Changwook Jeong ,  Sanghoon Myung ,  Min-Chul Park ,  Jeonghoon Ko ,  Jisu Ryu ,  Hyunjae Jang ,  Hyungtae Kim ,  Yunrong Li ,  Min Chul Jeon

IPC: G11C7/00 ,  G11C29/50 ,  G11C29/48 ,  G11C29/56 ,  G01R31/27 ,  G01R31/3185 ,  G01R31/30 ,  G01R31/26

Abstract: A fault analysis method of a semiconductor fault analysis device is provided. The fault analysis method includes: receiving measurement data measured corresponding to a semiconductor device; generating double sampling data based on the measurement data and reference data; performing a fault analysis operation with respect to the double sampling data; classifying a fault type of the semiconductor device based on a result of the fault analysis operation; and outputting information about the fault type.

公开(公告)号：US11574095B2

公开(公告)日：2023-02-07

申请号：US16906038

申请日：2020-06-19

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sanghoon Myung ,  Hyunjae Jang ,  In Huh ,  Hyeon Kyun Noh ,  Min-Chul Park ,  Changwook Jeong

IPC: G06F30/27 ,  G06N3/08 ,  G06N3/10 ,  G06N3/04 ,  G06F30/398

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

公开(公告)号：US20240211736A1

公开(公告)日：2024-06-27

申请号：US18542890

申请日：2023-12-18

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Minchul Park ,  Satbyul Kim ,  Seongryeol Kim ,  Younggu Kim ,  Yeji Kim ,  Hyunjae Jang ,  In Huh

IPC: G06N3/0464 ,  G06F11/00 ,  G06N3/08

CPC classification number: G06N3/0464 ,  G06F11/004 ,  G06N3/08 ,  G06F2201/86

Abstract: Provided are an apparatus and a method of inferring semiconductor measurement results. The method of inferring semiconductor measurement results is based on artificial intelligence techniques and includes receiving layout data representing a layout of a semiconductor, generating a plurality of partial layouts based on the layout data, selecting a representative partial layout among the plurality of partial layouts, and generating, using a machine learning model, a predicted measurement result for the semiconductor based on the representative partial layout.

公开(公告)号：US11886783B2

公开(公告)日：2024-01-30

申请号：US18153573

申请日：2023-01-12

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sanghoon Myung ,  Hyunjae Jang ,  In Huh ,  Hyeon Kyun Noh ,  Min-Chul Park ,  Changwook Jeong

IPC: G06F30/27 ,  G06N3/08 ,  G06N3/10 ,  G06F30/398 ,  G06N3/044

CPC classification number: G06F30/27 ,  G06F30/398 ,  G06N3/044 ,  G06N3/08 ,  G06N3/10

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

公开(公告)号：US20230142367A1

公开(公告)日：2023-05-11

申请号：US18153573

申请日：2023-01-12

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sanghoon MYUNG ,  Hyunjae Jang ,  In Huh ,  Hyeon Kyun Noh ,  Min-Chul Park ,  Changwook Jeong

IPC: G06F30/27 ,  G06N3/08 ,  G06N3/10 ,  G06F30/398 ,  G06N3/044

CPC classification number: G06F30/27 ,  G06N3/08 ,  G06N3/10 ,  G06F30/398 ,  G06N3/044

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

公开(公告)号：US20210158152A1

公开(公告)日：2021-05-27

申请号：US16906038

申请日：2020-06-19

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sanghoon MYUNG ,  Hyunjae Jang ,  In Huh ,  Hyeon Kyun Noh ,  Min-chul Park ,  Changwook Jeong

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/10

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.