KR20210069736A - 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 - Google Patents
블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 Download PDFInfo
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- KR20210069736A KR20210069736A KR1020217016889A KR20217016889A KR20210069736A KR 20210069736 A KR20210069736 A KR 20210069736A KR 1020217016889 A KR1020217016889 A KR 1020217016889A KR 20217016889 A KR20217016889 A KR 20217016889A KR 20210069736 A KR20210069736 A KR 20210069736A
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Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020237034866A KR20230147764A (ko) | 2018-11-02 | 2019-11-01 | 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 |
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201862754880P | 2018-11-02 | 2018-11-02 | |
| US62/754,880 | 2018-11-02 | ||
| US16/572,971 | 2019-09-17 | ||
| US16/572,971 US11468553B2 (en) | 2018-11-02 | 2019-09-17 | System and method for determining type and size of defects on blank reticles |
| PCT/US2019/059291 WO2020092856A1 (en) | 2018-11-02 | 2019-11-01 | System and method for determining type and size of defects on blank reticles |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020237034866A Division KR20230147764A (ko) | 2018-11-02 | 2019-11-01 | 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 |
Publications (1)
| Publication Number | Publication Date |
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| KR20210069736A true KR20210069736A (ko) | 2021-06-11 |
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| KR1020217016889A Ceased KR20210069736A (ko) | 2018-11-02 | 2019-11-01 | 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 |
| KR1020237034866A Pending KR20230147764A (ko) | 2018-11-02 | 2019-11-01 | 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 |
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| KR1020237034866A Pending KR20230147764A (ko) | 2018-11-02 | 2019-11-01 | 블랭크 레티클 상의 결함의 유형 및 크기를 결정하기 위한 시스템 및 방법 |
Country Status (7)
| Country | Link |
|---|---|
| US (1) | US11468553B2 (https=) |
| JP (1) | JP7355817B2 (https=) |
| KR (2) | KR20210069736A (https=) |
| CN (1) | CN112955732B (https=) |
| IL (1) | IL282249B2 (https=) |
| TW (1) | TWI805857B (https=) |
| WO (1) | WO2020092856A1 (https=) |
Families Citing this family (35)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11568331B2 (en) * | 2011-09-26 | 2023-01-31 | Open Text Corporation | Methods and systems for providing automated predictive analysis |
| US10522322B2 (en) | 2017-04-13 | 2019-12-31 | Fractilia, Llc | System and method for generating and analyzing roughness measurements |
| US12142454B2 (en) | 2017-04-13 | 2024-11-12 | Fractilla, LLC | Detection of probabilistic process windows |
| US10176966B1 (en) | 2017-04-13 | 2019-01-08 | Fractilia, Llc | Edge detection system |
| US11380516B2 (en) | 2017-04-13 | 2022-07-05 | Fractilia, Llc | System and method for generating and analyzing roughness measurements and their use for process monitoring and control |
| KR102610060B1 (ko) * | 2018-11-30 | 2023-12-06 | 에이에스엠엘 네델란즈 비.브이. | 제조성에 기초한 패터닝 디바이스 패턴을 결정하기 위한 방법 |
| AU2020379834A1 (en) | 2019-11-05 | 2022-06-09 | Strong Force Vcn Portfolio 2019, Llc | Control tower and enterprise management platform for value chain networks |
| US20210133670A1 (en) | 2019-11-05 | 2021-05-06 | Strong Force Vcn Portfolio 2019, Llc | Control tower and enterprise management platform with a machine learning/artificial intelligence managing sensor and the camera feeds into digital twin |
| WO2021092260A1 (en) | 2019-11-05 | 2021-05-14 | Strong Force Vcn Portfolio 2019, Llc | Control tower and enterprise management platform for value chain networks |
| US11769242B2 (en) | 2020-05-21 | 2023-09-26 | Kla Corporation | Mode selection and defect detection training |
| US11774371B2 (en) | 2020-05-22 | 2023-10-03 | Kla Corporation | Defect size measurement using deep learning methods |
| CN114175093A (zh) * | 2020-05-29 | 2022-03-11 | 京东方科技集团股份有限公司 | 显示面板的检测装置、检测方法、电子装置、可读介质 |
| WO2021243360A1 (en) * | 2020-05-29 | 2021-12-02 | Lam Research Corporation | Automated visual-inspection system |
| US11328410B2 (en) | 2020-08-03 | 2022-05-10 | KLA Corp. | Deep generative models for optical or other mode selection |
| EP3961335B1 (en) * | 2020-08-28 | 2024-07-17 | Siemens Aktiengesellschaft | System, apparatus and method for estimating remaining useful life of a bearing |
| CN112085722B (zh) * | 2020-09-07 | 2024-04-09 | 凌云光技术股份有限公司 | 一种训练样本图像获取方法及装置 |
| US20220122038A1 (en) * | 2020-10-20 | 2022-04-21 | Kyndryl, Inc. | Process Version Control for Business Process Management |
| US20220270212A1 (en) * | 2021-02-25 | 2022-08-25 | Kla Corporation | Methods for improving optical inspection and metrology image quality using chip design data |
| CN113109369A (zh) * | 2021-05-22 | 2021-07-13 | 盐城市盐都区荣海实验器材厂 | 一种载玻片的生产制备工艺 |
| US12026680B2 (en) * | 2021-09-01 | 2024-07-02 | Caterpillar Inc. | System and method for inferring machine failure, estimating when the machine will be repaired, and computing an optimal solution |
| CN113850766B (zh) * | 2021-09-10 | 2024-10-22 | 浙江博星工贸有限公司 | 凸轮轴表面缺陷检测方法、装置及计算机可读存储介质 |
| US20230153843A1 (en) * | 2021-11-12 | 2023-05-18 | Oracle International Corporation | System to combine intelligence from multiple sources that use disparate data sets |
| US12586171B2 (en) * | 2021-11-17 | 2026-03-24 | Communications Test Design, Inc. | Methods and systems for grading devices |
| TWI799083B (zh) * | 2022-01-14 | 2023-04-11 | 合晶科技股份有限公司 | 自動光學缺陷檢測裝置及方法 |
| JP2023129970A (ja) * | 2022-03-07 | 2023-09-20 | セイコーエプソン株式会社 | 印刷画像の欠陥判別装置、およびその判別方法 |
| US12406372B2 (en) * | 2022-05-10 | 2025-09-02 | Canon Medical Systems Corporation | Image processing apparatus, a method of processing image data, and a computer program product |
| US12581914B2 (en) * | 2022-06-09 | 2026-03-17 | Onto Innovation Inc. | Optical metrology with nuisance feature mitigation |
| US20240232770A9 (en) * | 2022-10-25 | 2024-07-11 | PTO Genius, LLC | Systems and methods for exhaustion mitigation and organization optimization |
| CN115713487A (zh) * | 2022-10-26 | 2023-02-24 | 上海船舶工艺研究所(中国船舶集团有限公司第十一研究所) | 用于x射线焊缝图像的缺陷识别方法、设备和存储介质 |
| US20240144464A1 (en) * | 2022-10-28 | 2024-05-02 | Applied Materials, Inc. | Classification of defect patterns of substrates |
| WO2024181209A1 (ja) * | 2023-02-27 | 2024-09-06 | パナソニックIpマネジメント株式会社 | 処理方法およびそれを利用した処理装置 |
| DE102023108878A1 (de) | 2023-04-06 | 2024-10-10 | Audi Aktiengesellschaft | Verfahren und Vorrichtung zum Prüfen einer flexiblen Leiterplatte, insbesondere bei Herstellung, auf Fehler |
| US12586085B2 (en) * | 2023-07-03 | 2026-03-24 | Ebay Inc. | Method for determining authenticity of hanging images and deformation analysis of authenticity of item based on authentication score transgressing authenticity threshold |
| US20250117915A1 (en) * | 2023-10-06 | 2025-04-10 | Applied Materials, Inc. | Optical inspection-based automatic defect classification |
| US20250363617A1 (en) * | 2024-05-24 | 2025-11-27 | Kla Corporation | System and method for defect detection using deep learning-based image segmentation |
Family Cites Families (32)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5161052B2 (ja) | 2008-12-04 | 2013-03-13 | オリンパス株式会社 | 顕微鏡システム、標本観察方法およびプログラム |
| US20040081350A1 (en) | 1999-08-26 | 2004-04-29 | Tadashi Kitamura | Pattern inspection apparatus and method |
| US6999614B1 (en) * | 1999-11-29 | 2006-02-14 | Kla-Tencor Corporation | Power assisted automatic supervised classifier creation tool for semiconductor defects |
| US6798515B1 (en) * | 2001-11-29 | 2004-09-28 | Cognex Technology And Investment Corporation | Method for calculating a scale relationship for an imaging system |
| US7162073B1 (en) | 2001-11-30 | 2007-01-09 | Cognex Technology And Investment Corporation | Methods and apparatuses for detecting classifying and measuring spot defects in an image of an object |
| US9002497B2 (en) | 2003-07-03 | 2015-04-07 | Kla-Tencor Technologies Corp. | Methods and systems for inspection of wafers and reticles using designer intent data |
| JP2007024737A (ja) * | 2005-07-20 | 2007-02-01 | Hitachi High-Technologies Corp | 半導体の欠陥検査装置及びその方法 |
| US7747062B2 (en) * | 2005-11-09 | 2010-06-29 | Kla-Tencor Technologies Corp. | Methods, defect review tools, and systems for locating a defect in a defect review process |
| JP4890096B2 (ja) | 2006-05-19 | 2012-03-07 | 浜松ホトニクス株式会社 | 画像取得装置、画像取得方法、及び画像取得プログラム |
| US20070280526A1 (en) * | 2006-05-30 | 2007-12-06 | Irfan Malik | Determining Information about Defects or Binning Defects Detected on a Wafer after an Immersion Lithography Process is Performed on the Wafer |
| US7831083B1 (en) * | 2006-07-13 | 2010-11-09 | Kla-Tencor Technologies Corporation | Image quality monitoring for substrate inspection |
| US8045145B1 (en) * | 2007-06-06 | 2011-10-25 | Kla-Tencor Technologies Corp. | Systems and methods for acquiring information about a defect on a specimen |
| JP2013072788A (ja) * | 2011-09-28 | 2013-04-22 | Hitachi High-Technologies Corp | 基板表面欠陥検査方法および検査装置 |
| WO2014074178A1 (en) * | 2012-11-08 | 2014-05-15 | The Johns Hopkins University | System and method for detecting and classifying severity of retinal disease |
| JP5948262B2 (ja) * | 2013-01-30 | 2016-07-06 | 株式会社日立ハイテクノロジーズ | 欠陥観察方法および欠陥観察装置 |
| JP5760066B2 (ja) * | 2013-11-06 | 2015-08-05 | 株式会社日立ハイテクノロジーズ | 欠陥検査装置及び欠陥検査方法 |
| US9401016B2 (en) | 2014-05-12 | 2016-07-26 | Kla-Tencor Corp. | Using high resolution full die image data for inspection |
| US10074036B2 (en) * | 2014-10-21 | 2018-09-11 | Kla-Tencor Corporation | Critical dimension uniformity enhancement techniques and apparatus |
| CN104715481B (zh) * | 2015-03-17 | 2017-07-25 | 西安交通大学 | 基于随机森林的多尺度印刷品缺陷检测方法 |
| US9959599B2 (en) * | 2015-06-18 | 2018-05-01 | Sharp Laboratories Of America, Inc. | System for enhanced images |
| TWI737659B (zh) * | 2015-12-22 | 2021-09-01 | 以色列商應用材料以色列公司 | 半導體試樣的基於深度學習之檢查的方法及其系統 |
| US10043261B2 (en) * | 2016-01-11 | 2018-08-07 | Kla-Tencor Corp. | Generating simulated output for a specimen |
| JP6673122B2 (ja) * | 2016-09-29 | 2020-03-25 | 株式会社Sumco | シリコンウェーハの評価方法、シリコンウェーハ製造工程の評価方法およびシリコンウェーハの製造方法 |
| TWI752100B (zh) * | 2016-10-17 | 2022-01-11 | 美商克萊譚克公司 | 用於訓練檢查相關演算法之系統、非暫時性電腦可讀媒體及電腦實施方法 |
| US11047806B2 (en) | 2016-11-30 | 2021-06-29 | Kla-Tencor Corporation | Defect discovery and recipe optimization for inspection of three-dimensional semiconductor structures |
| US10496781B2 (en) * | 2016-12-19 | 2019-12-03 | Kla Tencor Corporation | Metrology recipe generation using predicted metrology images |
| US10964013B2 (en) | 2017-01-10 | 2021-03-30 | Kla-Tencor Corporation | System, method for training and applying defect classifiers in wafers having deeply stacked layers |
| US10565702B2 (en) * | 2017-01-30 | 2020-02-18 | Dongfang Jingyuan Electron Limited | Dynamic updates for the inspection of integrated circuits |
| JP6705777B2 (ja) * | 2017-07-10 | 2020-06-03 | ファナック株式会社 | 機械学習装置、検査装置及び機械学習方法 |
| US10692203B2 (en) * | 2018-02-19 | 2020-06-23 | International Business Machines Corporation | Measuring defectivity by equipping model-less scatterometry with cognitive machine learning |
| US10706525B2 (en) * | 2018-05-22 | 2020-07-07 | Midea Group Co. Ltd. | Methods and systems for improved quality inspection |
| US10733723B2 (en) * | 2018-05-22 | 2020-08-04 | Midea Group Co., Ltd. | Methods and system for improved quality inspection |
-
2019
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| JP7355817B2 (ja) | 2023-10-03 |
| KR20230147764A (ko) | 2023-10-23 |
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| CN112955732B (zh) | 2024-08-20 |
| TW202029071A (zh) | 2020-08-01 |
| TWI805857B (zh) | 2023-06-21 |
| WO2020092856A1 (en) | 2020-05-07 |
| IL282249B1 (en) | 2024-10-01 |
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| US20200143528A1 (en) | 2020-05-07 |
| US11468553B2 (en) | 2022-10-11 |
| CN112955732A (zh) | 2021-06-11 |
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