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    Wafer Defect Discovery
    23.
    发明申请
    Wafer Defect Discovery 审中-公开
    晶圆缺陷发现

    公开(公告)号：US20170076911A1

    公开(公告)日：2017-03-16

    申请号：US15359589

    申请日：2016-11-22

    Applicant: KLA-Tencor Corporation

    Inventor： Hong Chen ,  Kenong Wu ,  Martin Plihal ,  Vidur Pandita ,  Ravikumar Sanapala ,  Vivek Bhagat ,  Rahul Lakhawat ,  Oksen Baris ,  Rajesh Ramachandran ,  Naoshin Haque

    IPC: H01J37/28

    CPC classification number: H01J37/28 ,  G01N21/8851 ,  G01N21/9501 ,  G01N2021/8854 ,  G01N2021/8883 ,  G03F7/70625 ,  G03F7/7065 ,  H01J2237/24592

    Abstract: Systems and methods for discovering defects on a wafer are provided. One method includes detecting defects on a wafer by applying a threshold to output generated by a detector in a first scan of the wafer and determining values for features of the detected defects. The method also includes automatically ranking the features, identifying feature cut-lines to group the defect into bins, and, for each of the bins, determining one or more parameters that if applied to the values for the features of the defects in each of the bins will result in a predetermined number of the defects in each of the bins. The method also includes applying the one or more determined parameters to the output generated by the detector in a second scan of the wafer to generate a defect population that has a predetermined defect count and is diversified in the values for the features.

    Abstract translation: 提供了发现晶片缺陷的系统和方法。 一种方法包括通过在晶片的第一次扫描中施加由检测器产生的输出的阈值来检测晶片上的缺陷，并确定检测到的缺陷的特征的值。 该方法还包括对特征进行自动排序，识别特征切割线以将缺陷分组成箱，并且对于每个箱，确定一个或多个参数，如果应用于每个中的缺陷的特征的值 箱将导致每个箱中预定数量的缺陷。 该方法还包括将一个或多个确定的参数应用于在晶片的第二次扫描中由检测器产生的输出，以产生具有预定缺陷计数并且在特征值中多样化的缺陷群体。

    Nuisance mining for novel defect discovery
    24.
    发明授权
    Nuisance mining for novel defect discovery 有权

    公开(公告)号：US11514357B2

    公开(公告)日：2022-11-29

    申请号：US16277617

    申请日：2019-02-15

    Applicant: KLA-TENCOR CORPORATION

    Inventor： Martin Plihal

    IPC: G06N20/00 ,  G01N21/95

    Abstract: A method of defect discovery can include providing a nuisance bin in a nuisance filter, partitioning the defect population into a defect population partition, segmenting the defect population partition into a defect population segment, selecting from the defect population segment a selected set of defects, computing one or more statistics of the signal attributes of the defects in the defect population segment, replicating the selected set of defects to yield generated defects, shifting the generated defects outside of the defect population segment, creating a training set, and training a binary classifier. This method can be operated on a system. The method can enable a semiconductor manufacturer to determine more accurately the presence of defects that would otherwise have gone unnoticed.

    And noise based care areas
    25.
    发明授权
    And noise based care areas 有权

    公开(公告)号：US10832396B2

    公开(公告)日：2020-11-10

    申请号：US16364161

    申请日：2019-03-25

    Applicant: KLA-Tencor Corporation

    Inventor： Brian Duffy ,  Martin Plihal ,  Santosh Bhattacharyya ,  Gordon Rouse ,  Chris Maher ,  Erfan Soltanmohammadi

    IPC: G03F1/84 ,  G06T7/00 ,  H01L21/66 ,  G06T7/11 ,  G03F7/20 ,  G01R31/308

    Abstract: Methods and systems for setting up inspection of a specimen with design and noise based care areas are provided. One system includes one or more computer subsystems configured for generating a design-based care area for a specimen. The computer subsystem(s) are also configured for determining one or more output attributes for multiple instances of the care area on the specimen, and the one or more output attributes are determined from output generated by an output acquisition subsystem for the multiple instances. The computer subsystem(s) are further configured for separating the multiple instances of the care area on the specimen into different care area sub-groups such that the different care area sub-groups have statistically different values of the output attribute(s) and selecting a parameter of an inspection recipe for the specimen based on the different care area sub-groups.

    Production sample shaping that preserves re-normalizability
    26.
    发明授权
    Production sample shaping that preserves re-normalizability 有权

    公开(公告)号：US10338004B2

    公开(公告)日：2019-07-02

    申请号：US14666942

    申请日：2015-03-24

    Applicant: KLA-Tencor Corporation

    Inventor： Martin Plihal ,  Ankit Jain ,  Michael Lennek

    IPC: G01N21/93 ,  G01N21/95 ,  H01L21/66

    Abstract: Methods and systems for generating defect samples are provided. One method includes identifying a set of defects detected on a wafer having the most diversity in values of at least one defect attribute and generating different tiles for different defects in the set. The tiles define a portion of all values for the at least one attribute of all defects detected on the wafer that are closer to the values for the at least one attribute of their corresponding defects than the values for the at least one attribute of other defects. In addition, the method includes separating the defects on the wafer into sample bins corresponding to the different tiles based on their values of the at least one attribute, randomly selecting defect(s) from each of two or more of the sample bins, and creating a defect sample for the wafer that includes the randomly selected defects.

    Adaptive nuisance filter
    28.
    发明授权
    Adaptive nuisance filter 有权

    公开(公告)号：US09835566B2

    公开(公告)日：2017-12-05

    申请号：US15058115

    申请日：2016-03-01

    Applicant: KLA-Tencor Corporation

    Inventor： Ardis Liang ,  Martin Plihal ,  Raghav Babulnath ,  Sankar Venkataraman

    IPC: G01N21/88 ,  G01N23/20 ,  G01N21/95

    CPC classification number: G01N21/8806 ,  G01N21/9501 ,  G01N23/20008 ,  G01N2021/8809 ,  G01N2201/061 ,  G01N2201/0683

    Abstract: Methods and systems for generating inspection results for a specimen with an adaptive nuisance filter are provided. One method includes selecting a portion of events detected during inspection of a specimen having values for at least one feature of the events that are closer to at least one value of at least one parameter of the nuisance filter than the values for at least one feature of another portion of the events. The method also includes acquiring output of an output acquisition subsystem for the sample of events, classifying the events in the sample based on the acquired output, and determining if one or more parameters of the nuisance filter should be modified based on results of the classifying. The nuisance filter or the modified nuisance filter can then be applied to results of the inspection of the specimen to generate final inspection results for the specimen.

    Unbiased Wafer Defect Samples
    30.
    发明申请
    Unbiased Wafer Defect Samples 有权
    无偏置晶圆缺陷样品

    公开(公告)号：US20140133737A1

    公开(公告)日：2014-05-15

    申请号：US13793709

    申请日：2013-03-11

    Applicant: KLA-TENCOR CORPORATION

    Inventor： Martin Plihal ,  Vidyasagar Anantha ,  Saravanan Paramasivam ,  Chris W. Lee

    IPC: G06T7/00

    CPC classification number: G06T7/0008 ,  F04C2270/0421 ,  G06T5/50 ,  G06T7/0004 ,  G06T2207/30148

    Abstract: Methods and systems for generating unbiased wafer defect samples are provided. One method includes selecting the defects detected by each of multiple scans performed on a wafer that have the most diversity in one or more defect attributes such that a diverse set of defects are selected across each scan. In addition, the method may include selecting the defects such that any defect that is selected and is common to two or more of the scans is not selected twice and any defects that are selected are diverse with respect to the common, selected defect. Furthermore, no sampling, binning, or classifying of the defects may be performed prior to selection of the defects such that the sampled defects are unbiased by any sampling, binning, or classifying method.

    Abstract translation: 提供了用于产生无偏置晶片缺陷样品的方法和系统。 一种方法包括选择通过在一个或多个缺陷属性中具有最多分集的晶片上执行的多次扫描中检测到的缺陷，从而跨越每个扫描选择不同的缺陷集。 此外，该方法可以包括选择缺陷，使得两个或更多个扫描选择并且是共同的任何缺陷不被选择两次，并且所选择的任何缺陷相对于共同的所选择的缺陷是多种多样的。 此外，在选择缺陷之前，可以不进行采样，分类或缺陷分类，以便通过任何采样，合并或分类方法对采样缺陷进行不偏见。

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