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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
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.
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公开(公告)号:US11853660B2
公开(公告)日:2023-12-26
申请号:US17231428
申请日:2021-04-15
Applicant: Samsung Electronics Co., Ltd.
Inventor: Hyunjoong Kim , Jaepil Shin , Moonhyun Cha , Changwook Jeong
IPC: H01L21/027 , G06F30/39 , G06F30/27 , G06N3/08 , G06N3/045 , G06F119/02 , G06F119/18
CPC classification number: G06F30/27 , G06N3/045 , G06N3/08 , G06F2119/02 , G06F2119/18
Abstract: A system for modeling a semiconductor fabrication process includes at least one first processor and at least one second processor. The at least one first processor is configured to provide at least one machine learning (ML) model, which is trained by using a plurality of pairs of images of a design pattern sample and a physical pattern sample. The physical pattern sample is formed from the design pattern sample by using the semiconductor fabrication process. The at least one second processor is configured to provide an input image representing a shape of a design pattern and/or a physical pattern to the at least one first processor and to generate output data defining the physical pattern and/or the design pattern based on an output image received from the at least one first processor.
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公开(公告)号:US20210405521A1
公开(公告)日:2021-12-30
申请号:US17180984
申请日:2021-02-22
Applicant: Samsung Electronics Co., Ltd.
Inventor: Taehoon Kim , Jaeho Jeong , Jeonghoon Ko , Jongwon Kim , Yejin Jeong , Changwook Jeong
IPC: G03F1/36 , G03F7/20 , H01L21/027
Abstract: A proximity correction method for a semiconductor manufacturing process includes: generating a plurality of pieces of original image data from a plurality of sample regions, with the sample regions selected from layout data used in the semiconductor manufacturing process; removing some pieces of original image data that overlap with each other from the plurality of pieces of original image data, resulting in a plurality of pieces of input image data; inputting the plurality of pieces of input image data to a machine learning model; obtaining a prediction value of critical dimensions of target patterns included in the plurality of pieces of input image data from the machine learning model; measuring a result value for critical dimensions of actual patterns corresponding to the target patterns on a semiconductor substrate on which the semiconductor manufacturing process is performed; and performing learning of the machine learning model using the prediction value and the result value.
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公开(公告)号:US20210117193A1
公开(公告)日:2021-04-22
申请号:US16915786
申请日:2020-06-29
Applicant: Samsung Electronics Co., Ltd.
Inventor: Seungju Kim , Hyojin Choi , In Huh , Jeonghoon Ko , Changwook Jeong , Younsik Park , Joonwan Chai
Abstract: An electronic device configured to generate a verification vector for verifying a semiconductor circuit including a first circuit block and a second circuit block includes a duplicate command eliminator configured to receive a first input vector including a plurality of commands and to provide a first converted vector, in which ones of the plurality of commands that generate the same state transition are changed into idle commands, based on a state transition of the first circuit block obtained by performing a simulation operation on the first input vector, a reduced vector generator configured to provide a first reduced vector in which a number of repetitions of the idle commands included in the first converted vector is reduced, and a verification vector generator configured to output the first reduced vector having a coverage that coincides with a target coverage among a plurality of first reduced vectors as a first verification vector.
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公开(公告)号:US12175177B2
公开(公告)日:2024-12-24
申请号:US16694498
申请日:2019-11-25
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Jun Haeng Lee , Youngmin Oh , Hyun Sun Park , Yongwoo Lee , Jaecheol Lee , Hyojin Choi , Younsik Park , Seungju Kim , Changwook Jeong , In Huh
Abstract: A system verification method includes generating a first verification vector as a result of a first action of an agent, the first verification vector referring to an observation corresponding to at least one state already covered, from among states of elements of a target system, identifying a first coverage corresponding to at least one state covered by the first verification vector, from among the states of the elements, updating the observation by reflecting the first coverage in the observation, and generating a second verification vector through a second action of the agent, the second verification vector referring to the updated observation.
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公开(公告)号:US11741596B2
公开(公告)日:2023-08-29
申请号:US16599733
申请日:2019-10-11
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Min-Chul Park , Ami Ma , Jisu Ryu , Changwook Jeong
IPC: G06K9/00 , G06T7/00 , H01L21/67 , G01N21/956 , G01N21/95 , G06T5/00 , G01N21/88 , G06V10/70 , G06V10/82 , G06V10/74
CPC classification number: G06T7/001 , G01N21/8851 , G01N21/9501 , G01N21/95607 , G06T5/002 , G06T7/0004 , G06V10/70 , G06V10/74 , G06V10/82 , H01L21/67288 , G01N2021/8854 , G01N2021/8867 , G01N2021/95615 , G06T2207/20081 , G06T2207/30141 , G06T2207/30148
Abstract: A semiconductor wafer fault analysis system includes: a database to store a first reference map, which is classified as a first fault type, and a second reference map, which is classified as a second fault type; a first auto-encoder/decoder to remove a noise corresponding to the first fault type from the first reference map to generate a first pre-processed reference map; a second auto-encoder/decoder to remove a noise corresponding to the second fault type from the second reference map to generate a second pre-processed reference map; and a fault type analyzer. The database is updated based on the first and second pre-processed reference maps, and the fault type analyzer is to classify a fault type of a target map based on the updated database. The target map is generated by measuring a target wafer.
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公开(公告)号:US20220092239A1
公开(公告)日:2022-03-24
申请号:US17231428
申请日:2021-04-15
Applicant: Samsung Electronics Co., Ltd.
Inventor: Hyunjoong Kim , Jaepil Shin , Moonhyun Cha , Changwook Jeong
Abstract: A system for modeling a semiconductor fabrication process includes at least one first processor and at least one second processor. The at least one first processor is configured to provide at least one machine learning (ML) model, which is trained by using a plurality of pairs of images of a design pattern sample and a physical pattern sample. The physical pattern sample is formed from the design pattern sample by using the semiconductor fabrication process. The at least one second processor is configured to provide an input image representing a shape of a design pattern and/or a physical pattern to the at least one first processor and to generate output data defining the physical pattern and/or the design pattern based on an output image received from the at least one first processor.
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公开(公告)号:US11775840B2
公开(公告)日:2023-10-03
申请号:US16909132
申请日:2020-06-23
Applicant: Samsung Electronics Co., Ltd.
Inventor: Wonik Jang , Sanghoon Myung , Changwook Jeong , Sunghee Lee
Abstract: A non-transitory computer-readable medium storing a program code including an image generation model, which when executed, causes a processor to input input data including sampling data of some of a plurality of semiconductor dies of a wafer to a generator network of the image generation model and output a wafer map indicating the plurality of semiconductor dies, and to input the wafer map output from the generator network to a discriminator network of the image generation model and discriminate the wafer map.
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公开(公告)号:US11733603B2
公开(公告)日:2023-08-22
申请号:US17180984
申请日:2021-02-22
Applicant: Samsung Electronics Co., Ltd.
Inventor: Taehoon Kim , Jaeho Jeong , Jeonghoon Ko , Jongwon Kim , Yejin Jeong , Changwook Jeong
IPC: G03F1/36 , H01L21/027 , G03F7/20 , G03F7/00
CPC classification number: G03F1/36 , G03F7/70441 , G03F7/70625 , H01L21/027
Abstract: A proximity correction method for a semiconductor manufacturing process includes: generating a plurality of pieces of original image data from a plurality of sample regions, with the sample regions selected from layout data used in the semiconductor manufacturing process; removing some pieces of original image data that overlap with each other from the plurality of pieces of original image data, resulting in a plurality of pieces of input image data; inputting the plurality of pieces of input image data to a machine learning model; obtaining a prediction value of critical dimensions of target patterns included in the plurality of pieces of input image data from the machine learning model; measuring a result value for critical dimensions of actual patterns corresponding to the target patterns on a semiconductor substrate on which the semiconductor manufacturing process is performed; and performing learning of the machine learning model using the prediction value and the result value.
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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.
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