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公开(公告)号：US10074167B2
公开(公告)日：2018-09-11
申请号：US15355509
申请日：2016-11-18
Applicant: KLA-Tencor Corporation
Inventor： Saibal Banerjee , Ashok Kulkarni , Shaoyu Lu
IPC: G06T7/00
CPC classification number: G06T7/0004 , G06T7/001 , G06T7/337 , G06T2207/10061 , G06T2207/30148
Abstract: Noise induced by pattern-of-interest (POI) image registration and POI vicinity design patterns in intra-die inspection is reduced. POI are grouped into alignment groups by co-occurrence of proximate registration targets. The alignment groups are registered using the co-occurrence of proximate registration targets. Registration by voting is performed, which can measure a degree that each of the patterns-of-interest is an outlier. POI are grouped into at least one vicinity group with same vicinity design effects.
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公开(公告)号：US09767548B2
公开(公告)日：2017-09-19
申请号：US15135465
申请日：2016-04-21
Applicant: KLA-Tencor Corporation
Inventor： Saibal Banerjee , Ashok V. Kulkarni
CPC classification number: G06T7/001 , G06T2207/20021 , G06T2207/30148
Abstract: Methods and systems for identifying outliers in multiple instances of a pattern of interest (POI) are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a POI within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for determining a feature of each of the images generated at the multiple instances of the POI. In addition, the computer subsystem(s) are configured for identifying one or more outliers in the multiple instances of the POI based on the determined features.
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3.发明申请公开(公告)号：US20170206650A1
公开(公告)日：2017-07-20
申请号：US15356729
申请日：2016-11-21
Applicant: KLA-Tencor Corporation
Inventor： Ashok Kulkarni , Saibal Banerjee , Santosh Bhattacharyya , Bjorn Brauer
IPC: G06T7/00
CPC classification number: G06T7/0006 , G06T7/001 , G06T2207/10061 , G06T2207/30148
Abstract: Criticality of a detected defect can be determined based on context codes. The context codes can be generated for a region, each of which may be part of a die. Noise levels can be used to group context codes. The context codes can be used to automatically classify a range of design contexts present on a die without needing certain information a priori.
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公开(公告)号：US20170161888A1
公开(公告)日：2017-06-08
申请号：US15355509
申请日：2016-11-18
Applicant: KLA-Tencor Corporation
Inventor： Saibal Banerjee , Ashok Kulkarni , Shaoyu Lu
IPC: G06T7/00
CPC classification number: G06T7/0004 , G06T7/001 , G06T7/337 , G06T2207/10061 , G06T2207/30148
Abstract: Noise induced by pattern-of-interest (POI) image registration and POI vicinity design patterns in intra-die inspection is reduced. POI are grouped into alignment groups by co-occurrence of proximate registration targets. The alignment groups are registered using the co-occurrence of proximate registration targets. Registration by voting is performed, which can measure a degree that each of the patterns-of-interest is an outlier. POI are grouped into at least one vicinity group with same vicinity design effects.
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5.发明授权Adaptive sampling for semiconductor inspection recipe creation, defect review, and metrology 有权用于半导体检查配方创建，缺陷检查和计量的自适应采样公开(公告)号：US09098891B2
公开(公告)日：2015-08-04
申请号：US14228023
申请日：2014-03-27
Applicant: KLA-Tencor Corporation
Inventor： Ashok V. Kulkarni , Saibal Banerjee
CPC classification number: G06T7/0004 , G06T2207/10061 , G06T2207/30148
Abstract: Methods and systems for adaptive sampling for semiconductor inspection recipe creation, defect review, and metrology are provided. The embodiments provide image processing and pattern recognition algorithms and an adaptive sampling method for extracting critical areas from SEM image patches for use in a wafer inspection system when design data for a semiconductor chip is not available. The embodiments also provide image processing and pattern recognition algorithms for efficiently discovering critical defects and significant deviations in the normal manufacturing process, using the output from a wafer inspection system and an adaptive sampling method to select wafer locations to be examined on a high resolution review or metrology tool.
Abstract translation: 提供了用于半导体检测配方创建，缺陷检查和计量的自适应采样的方法和系统。 实施例提供了图像处理和模式识别算法以及用于在半导体芯片的设计数据不可用时从用于晶片检查系统的SEM图像补片提取临界区域的自适应采样方法。 实施例还提供图像处理和模式识别算法，用于在正常制造过程中有效地发现关键缺陷和显着偏差，使用晶片检查系统的输出和自适应采样方法来选择要在高分辨率检查中检查的晶片位置， 计量工具
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Patent Agency Ranking
公开(公告)号：US10714366B2
公开(公告)日：2020-07-14
申请号：US16375851
申请日：2019-04-04
Applicant: KLA-Tencor Corporation
Inventor： Saibal Banerjee , Jagdish Chandra Saraswatula
IPC: G03F7/20 , H01L21/67 , G01N21/95 , H01J37/22 , G01N21/956 , G06F30/398
Abstract: Methods and systems for shape metric based scoring of wafer locations are provided. One method includes selecting shape based grouping (SBG) rules for at least two locations on a wafer. For one of the wafer locations, the selecting step includes modifying distances between geometric primitives in a design for the wafer with metrology data for the one location and determining metrical complexity (MC) scores for SBG rules associated with the geometric primitives in a field of view centered on the one location based on the distances. The selecting step also includes selecting one of the SBG rules for the one location based on the MC scores. The method also includes sorting the at least two locations on the wafer based on the SBG rule selected for the at least two locations.
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公开(公告)号：US10416088B2
公开(公告)日：2019-09-17
申请号：US15784187
申请日：2017-10-16
Applicant: KLA-Tencor Corporation
Inventor： Brian Duffy , Saibal Banerjee
Abstract: Methods and systems for determining one or more characteristics for defects detected on a specimen are provided. One system includes one or more computer subsystems configured for identifying a first defect that was detected on a specimen by an inspection system with a first mode but was not detected with one or more other modes. The computer subsystem(s) are also configured for acquiring, from the storage medium, one or more images generated with the one or more other modes at a location on the specimen corresponding to the first defect. In addition, the computer subsystem(s) are configured for determining one or more characteristics of the acquired one or more images and determining one or more characteristics of the first defect based on the one or more characteristics of the acquired one or more images.
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公开(公告)号：US20180052118A1
公开(公告)日：2018-02-22
申请号：US15784187
申请日：2017-10-16
Applicant: KLA-Tencor Corporation
Inventor： Brian Duffy , Saibal Banerjee
CPC classification number: G01N21/8851 , G01N21/9501 , G01N2021/8887 , H01J37/222 , H01J37/26 , H01J37/28 , H01J2237/22 , H01J2237/221 , H01J2237/26 , H01J2237/2817
Abstract: Methods and systems for determining one or more characteristics for defects detected on a specimen are provided. One system includes one or more computer subsystems configured for identifying a first defect that was detected on a specimen by an inspection system with a first mode but was not detected with one or more other modes. The computer subsystem(s) are also configured for acquiring, from the storage medium, one or more images generated with the one or more other modes at a location on the specimen corresponding to the first defect. In addition, the computer subsystem(s) are configured for determining one or more characteristics of the acquired one or more images and determining one or more characteristics of the first defect based on the one or more characteristics of the acquired one or more images.
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公开(公告)号：US09816939B2
公开(公告)日：2017-11-14
申请号：US14803872
申请日：2015-07-20
Applicant: KLA-Tencor Corporation
Inventor： Brian Duffy , Saibal Banerjee
CPC classification number: G01N21/8851 , G01N21/9501 , G01N2021/8887 , H01J37/222 , H01J37/26 , H01J37/28 , H01J2237/22 , H01J2237/221 , H01J2237/26 , H01J2237/2817
Abstract: Methods and systems for determining one or more characteristics for defects detected on a specimen are provided. One system includes one or more computer subsystems configured for identifying a first defect that was detected on a specimen by an inspection system with a first mode but was not detected with one or more other modes. The computer subsystem(s) are also configured for acquiring, from the storage medium, one or more images generated with the one or more other modes at a location on the specimen corresponding to the first defect. In addition, the computer subsystem(s) are configured for determining one or more characteristics of the acquired one or more images and determining one or more characteristics of the first defect based on the one or more characteristics of the acquired one or more images.
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10.发明申请Adaptive Sampling for Semiconductor Inspection Recipe Creation, Defect Review, and Metrology 有权半导体检测配方创建，缺陷评估和计量学的自适应采样公开(公告)号：US20140301630A1
公开(公告)日：2014-10-09
申请号：US14228023
申请日：2014-03-27
Applicant: KLA-Tencor Corporation
Inventor： Ashok V. Kulkarni , Saibal Banerjee
IPC: G06T7/00
CPC classification number: G06T7/0004 , G06T2207/10061 , G06T2207/30148
Abstract: Methods and systems for adaptive sampling for semiconductor inspection recipe creation, defect review, and metrology are provided. The embodiments provide image processing and pattern recognition algorithms and an adaptive sampling method for extracting critical areas from SEM image patches for use in a wafer inspection system when design data for a semiconductor chip is not available. The embodiments also provide image processing and pattern recognition algorithms for efficiently discovering critical defects and significant deviations in the normal manufacturing process, using the output from a wafer inspection system and an adaptive sampling method to select wafer locations to be examined on a high resolution review or metrology tool.
Abstract translation: 提供了用于半导体检测配方创建，缺陷检查和计量的自适应采样的方法和系统。 实施例提供了图像处理和模式识别算法以及用于在半导体芯片的设计数据不可用时从用于晶片检查系统的SEM图像补片提取临界区域的自适应采样方法。 实施例还提供图像处理和模式识别算法，用于在正常制造过程中有效地发现关键缺陷和显着偏差，使用晶片检查系统的输出和自适应采样方法来选择要在高分辨率检查中检查的晶片位置， 计量工具
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