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公开(公告)号：US20200372631A1
公开(公告)日：2020-11-26
申请号：US16993869
申请日：2020-08-14
Applicant: Applied Materials Israel, Ltd.
Inventor： Assaf ASBAG , Orly ZVITIA , Idan KAIZERMAN , Efrat ROSENMAN
Abstract: There are provided system and method of classifying defects in a specimen. The method includes: obtaining one or more defect clusters detected on a defect map of the specimen, each cluster characterized by a set of cluster attributes comprising spatial attributes including spatial density indicative of density of defects in one or more regions accommodating the cluster, each given defect cluster being detected at least based on the spatial density thereof meeting a criterion. The defect map also comprises non-clustered defects. Defects of interest (DOI) are identified in each cluster by performing respective defect filtrations for each cluster and non-clustered defects.
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公开(公告)号：US20190355628A1
公开(公告)日：2019-11-21
申请号：US16429533
申请日：2019-06-03
Applicant: Applied Materials Israel Ltd.
Inventor： Idan KAIZERMAN , Yotam SOFER
IPC: H01L21/66 , G03F7/20 , H01J37/304 , H01J37/317 , H01J37/28 , H01J37/22
Abstract: A method for process analysis includes acquiring first inspection data, using a first inspection modality, with respect to a substrate having multiple instances of a predefined pattern of features formed thereon using different, respective sets of process parameters. Characteristics of defects identified in the first inspection data are processed so as to select a first set of defect locations in which the first inspection data are indicative of an influence of the process parameters on the defects. Second inspection data are acquired, using a second inspection modality having a finer resolution than the first inspection modality, of the substrate at the locations in the first set. The defects appearing in the second inspection data are analyzed so as to select, from within the first set of the locations, a second set of the locations in which the second inspection data are indicative of an optimal range of the process parameters.
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公开(公告)号：US20160284579A1
公开(公告)日：2016-09-29
申请号：US14666183
申请日：2015-03-23
Applicant: Applied Materials Israel Ltd.
Inventor： Idan KAIZERMAN , Yotam SOFER
CPC classification number: H01L22/12 , G03F7/70558 , G03F7/70641 , G03F7/7065 , H01J37/222 , H01J37/28 , H01J37/304 , H01J37/3174 , H01J2237/221 , H01J2237/2817 , H01J2237/30416 , H01J2237/30433 , H01J2237/30461 , H01J2237/31798 , H01L22/20
Abstract: A method for process analysis includes acquiring first inspection data, using a first inspection modality, with respect to a substrate having multiple instances of a predefined pattern of features formed thereon using different, respective sets of process parameters. Characteristics of defects identified in the first inspection data are processed so as to select a first set of defect locations in which the first inspection data are indicative of an influence of the process parameters on the defects. Second inspection data are acquired, using a second inspection modality having a finer resolution than the first inspection modality, of the substrate at the locations in the first set. The defects appearing in the second inspection data are analyzed so as to select, from within the first set of the locations, a second set of the locations in which the second inspection data are indicative of an optimal range of the process parameters.
Abstract translation: 一种用于处理分析的方法包括：使用第一检查模式，使用不同的各组工艺参数，获得关于其上形成有预定图案特征的多个实例的基板的第一检查数据。 处理在第一检查数据中识别的缺陷的特征，以便选择第一组缺陷位置，其中第一检查数据表示处理参数对缺陷的影响。 使用具有比第一检查模式更精细的分辨率的第二检查模式在第一组中的位置获取第二检查数据。 分析出现在第二检查数据中的缺陷，以从第一组位置内选择第二组位置，其中第二检查数据表示过程参数的最佳范围。
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4.发明申请公开(公告)号：US20190066290A1
公开(公告)日：2019-02-28
申请号：US15685974
申请日：2017-08-24
Applicant: APPLIED MATERIALS ISRAEL LTD.
Inventor： Ohad SHAUBI , Assaf ASBAG , Idan KAIZERMAN
CPC classification number: G06T7/0004 , G05B23/00 , G06K9/6256 , G06K9/6262 , G06K9/6269 , G06N20/00 , G06N20/10 , G06N20/20 , G06T2207/30148
Abstract: There are provided a system, computer software product and method of generating a training set for a classifier using a processor. The method comprises: receiving a training set comprising training defects each having assigned attribute values, the training defects externally classified into classes comprising first and second major classes and a minor class; training a classifier upon the training set; receiving results of automatic classification of the training defects; automatically identifying a first defect that was externally classified into the first major class and automatically classified into the second major class; automatically identifying by the processor a second defect from the multiplicity of training defects that was externally classified into the minor class and automatically classified to the first or second major classes; and correcting the training set to include the first defect into the second major class, or to include the second defect into the first or the second major class.
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公开(公告)号：US20160035076A1
公开(公告)日：2016-02-04
申请号：US14446295
申请日：2014-07-29
Applicant: Applied Materials Israel Ltd.
Inventor： Ishai SCHWARZBAND , Yan IVANCHENKO , Daniel RAVID , Orly ZVITIA , Idan KAIZERMAN
CPC classification number: G06T7/001 , G06K9/4604 , G06K9/6211 , G06K2209/19 , G06K2209/403 , G06T2207/10028 , G06T2207/10061 , G06T2207/30148
Abstract: A method for image processing includes providing a microscopic image of a structure fabricated on a substrate and computer-aided design (CAD) data used in fabricating the structure. The microscopic image is processed by a computer so as to generate a first directionality map, which includes, for a matrix of points in the microscopic image, respective directionality vectors corresponding to magnitudes and directions of edges at the points irrespective of a sign of the magnitudes. The CAD data are processed by the computer so as to produce a simulated image based on the CAD data and to generate a second directionality map based on the simulated image. The first and second directionality maps are compared by the computer so as to register the microscopic image with the CAD data.
Abstract translation: 一种用于图像处理的方法包括提供在基板上制造的结构的微观图像和用于制造该结构的计算机辅助设计（CAD）数据。 显微镜图像由计算机处理，以便产生第一方向性图，其包括对于微观图像中的点的矩阵，对应于点处的边缘的大小和方向的各个方向性矢量，而不管幅度的符号 。 CAD数据由计算机处理，以便根据CAD数据产生模拟图像，并且基于模拟图像产生第二方向性图。 通过计算机比较第一和第二方向性图，以便将CAD数据注册到微观图像。
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Patent Agency Ranking
6.发明申请公开(公告)号：US20220067523A1
公开(公告)日：2022-03-03
申请号：US17521499
申请日：2021-11-08
Applicant: Applied Materials Israel Ltd.
Inventor： Leonid KARLINSKY , Boaz COHEN , Idan KAIZERMAN , Efrat ROSENMAN , Amit BATIKOFF , Daniel RAVID , Moshe ROSENWEIG
Abstract: A computerized system and method of training a deep neural network (DNN) is provided. The DNN is trained in a first training cycle using a first training set including first training samples. Each first training sample includes at least one first training image synthetically generated based on design data. Upon receiving a user feedback with respect to the DNN trained using the first training set, a second training cycle is adjusted based on the user feedback by obtaining a second training set including augmented training samples. The DNN is re-trained using the second training set. The augmented training samples are obtained by augmenting at least part of the first training samples using defect-related synthetic data. The trained DNN is usable for examination of a semiconductor specimen.
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公开(公告)号：US20190333208A1
公开(公告)日：2019-10-31
申请号：US15962909
申请日：2018-04-25
Applicant: Applied Materials Israel, Ltd.
Inventor： Assaf ASBAG , Orly ZVITIA , Idan KAIZERMAN , Efrat ROSENMAN
Abstract: There are provided system and method of classifying defects in a specimen. The method includes: obtaining one or more defect clusters detected on a defect map of the specimen, each cluster characterized by a set of cluster attributes comprising spatial attributes including spatial density indicative of density of defects in one or more regions accommodating the cluster, each given defect cluster being detected at least based on the spatial density thereof meeting a criterion; for each cluster, applying a cluster classifier to a respective set of cluster attributes thereof to associate the cluster with one or more labels of a predefined set of labels, wherein the cluster classifier is trained using cluster training data; and identifying DOI in each cluster by performing a defect filtration for each cluster using one or more filtering parameters specified in accordance with the label of the cluster.
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8.发明申请公开(公告)号：US20170357895A1
公开(公告)日：2017-12-14
申请号：US15668623
申请日：2017-08-03
Applicant: Applied Materials Israel Ltd.
Inventor： Leonid KARLINSKY , Boaz COHEN , Idan KAIZERMAN , Efrat ROSENMAN , Amit BATIKOFF , Daniel RAVID , Moshe ROSENWEIG
IPC: G06N3/08
CPC classification number: G06N3/08 , G06K9/036 , G06K9/4628 , G06K9/6271 , G06N3/0454
Abstract: There are provided system and method of segmentation a fabrication process (FP) image obtained in a fabrication of a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained to provide segmentation-related data, processing a fabrication process (FP) sample using the obtained trained DNN and, resulting from the processing, obtaining by the computer segments-related data characterizing the FP image to be segmented, the obtained segments-related data usable for automated examination of the semiconductor specimen. The DNN is trained using a segmentation training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprises a training image; FP sample comprises the FP image to be segmented.
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9.发明申请公开(公告)号：US20190234887A1
公开(公告)日：2019-08-01
申请号：US16227453
申请日：2018-12-20
Applicant: Applied Materials Israel Ltd.
Inventor： Idan KAIZERMAN , Mark GESHEL
Abstract: Data indicative of alignment targets may be received. Each alignment target may be associated with a target location on an object. Locations of the object to be inspected may be identified. An alignment target from the alignment targets may be selected. Each of the locations may be within a determined distance from the selected alignment target. An indication may be provided to align the object relative to an examination tool for inspecting the locations within the determined distance from the selected alignment target.
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公开(公告)号：US20180306728A1
公开(公告)日：2018-10-25
申请号：US15343090
申请日：2016-11-03
Applicant: Applied Materials Israel Ltd.
Inventor： Yotam SOFER , Idan KAIZERMAN
CPC classification number: G01N21/8851 , G01N21/9501 , G01N2021/8858
Abstract: Examining an object, comprising: receiving potential defects, each associated with a location; performing first clustering of the potential defects to obtain first and second subsets, the clustering performed such that potential defects in the first subset are denser in a physical area than potential defects in the second subset; automatically assigning first validity probabilities to potential defects in the first and second subsets; selecting for review potential defects from the first and second subsets, according to a third policy, and in accordance with a strategy for combining top elements and randomly selected elements from the merged list; receiving indications for potential defects in part of the potential defect lists, subsequent to potential defects being reviewed; updating the policies in accordance with validation or classification of items in the first and second subsets; and repeating said assigning, selecting, receiving and updating with the updated policies, until a stopping criteria is observed.
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