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    Based sampling and binning for yield critical defects
    1.
    发明授权
    Based sampling and binning for yield critical defects 有权
    用于产量关键缺陷的基于抽样和合并

    公开(公告)号：US09563943B2

    公开(公告)日：2017-02-07

    申请号：US15092510

    申请日：2016-04-06

    Applicant: KLA-Tencor Corporation

    Inventor： Satya Kurada ,  Raghav Babulnath ,  Kwok Ng ,  Lisheng Gao

    IPC: G06K9/00 ,  G06T7/00 ,  G01N21/956 ,  G01N21/95

    CPC classification number: G06T7/0006 ,  G01N21/9501 ,  G01N21/956 ,  G01N21/95607 ,  G01N2021/95676 ,  G01N2201/06113 ,  G01N2201/068 ,  G01N2201/10 ,  G01N2201/12 ,  G06K9/00 ,  G06K9/66 ,  G06T7/0008 ,  G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

    Abstract: Methods and systems for design based sampling and binning for yield critical defects are provided. One method includes aligning each image patch in each inspection image frame generated for a wafer by an optical subsystem of an inspection system to design information for the wafer. The method also includes deriving multiple layer design attributes at locations of defects detected in the image patches. In addition, the method includes building a decision tree with the multiple layer design attributes. The decision tree is used to separate the defects into bins with different yield impacts on a device being formed on the wafer. The method also includes binning the defects with the decision tree.

    Abstract translation: 提供了用于产量关键缺陷的基于设计的抽样和装箱的方法和系统。 一种方法包括通过检查系统的光学子系统对于为晶片生成的每个检查图像帧中的每个图像补片进行对准以设计晶片的信息。 该方法还包括在图像斑块中检测到的缺陷位置导出多层设计属性。 另外，该方法包括使用多层设计属性构建决策树。 决策树用于将缺陷分离成对晶片上形成的器件产生不同产量的影响。 该方法还包括使用决策树将缺陷合并。

    Based sampling and binning for yield critical defects
    2.
    发明授权
    Based sampling and binning for yield critical defects 有权
    用于产量关键缺陷的基于抽样和合并

    公开(公告)号：US09310320B2

    公开(公告)日：2016-04-12

    申请号：US14251415

    申请日：2014-04-11

    Applicant: KLA-Tencor Corporation

    Inventor： Satya Kurada ,  Raghav Babulnath ,  Kwok Ng ,  Lisheng Gao

    IPC: G06K9/00 ,  G01N21/956 ,  G06T7/00 ,  G01N21/95

    CPC classification number: G06T7/0006 ,  G01N21/9501 ,  G01N21/956 ,  G01N21/95607 ,  G01N2021/95676 ,  G01N2201/06113 ,  G01N2201/068 ,  G01N2201/10 ,  G01N2201/12 ,  G06K9/00 ,  G06K9/66 ,  G06T7/0008 ,  G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

    Abstract: Methods and systems for design based sampling and binning for yield critical defects are provided. One method includes aligning each image patch in each inspection image frame generated for a wafer by an optical subsystem of an inspection system to design information for the wafer. The method also includes deriving multiple layer design attributes at locations of defects detected in the image patches. In addition, the method includes building a decision tree with the multiple layer design attributes. The decision tree is used to separate the defects into bins with different yield impacts on a device being formed on the wafer. The method also includes binning the defects with the decision tree.

    Abstract translation: 提供了用于产量关键缺陷的基于设计的抽样和装箱的方法和系统。 一种方法包括通过检查系统的光学子系统对于为晶片生成的每个检查图像帧中的每个图像补片进行对准以设计晶片的信息。 该方法还包括在图像斑块中检测到的缺陷位置导出多层设计属性。 另外，该方法包括使用多层设计属性构建决策树。 决策树用于将缺陷分离成对晶片上形成的器件产生不同产量的影响。 该方法还包括使用决策树将缺陷合并。

    Design Based Sampling and Binning for Yield Critical Defects
    3.
    发明申请
    Design Based Sampling and Binning for Yield Critical Defects 有权
    基于设计的采样和分拣产量关键缺陷

    公开(公告)号：US20160225138A1

    公开(公告)日：2016-08-04

    申请号：US15092510

    申请日：2016-04-06

    Applicant: KLA-Tencor Corporation

    Inventor： Satya Kurada ,  Raghav Babulnath ,  Kwok Ng ,  Lisheng Gao

    IPC: G06T7/00 ,  G01N21/956 ,  G01N21/95

    CPC classification number: G06T7/0006 ,  G01N21/9501 ,  G01N21/956 ,  G01N21/95607 ,  G01N2021/95676 ,  G01N2201/06113 ,  G01N2201/068 ,  G01N2201/10 ,  G01N2201/12 ,  G06K9/00 ,  G06K9/66 ,  G06T7/0008 ,  G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

    Abstract: Methods and systems for design based sampling and binning for yield critical defects are provided. One method includes aligning each image patch in each inspection image frame generated for a wafer by an optical subsystem of an inspection system to design information for the wafer. The method also includes deriving multiple layer design attributes at locations of defects detected in the image patches. In addition, the method includes building a decision tree with the multiple layer design attributes. The decision tree is used to separate the defects into bins with different yield impacts on a device being formed on the wafer. The method also includes binning the defects with the decision tree.

    Abstract translation: 提供了用于产量关键缺陷的基于设计的抽样和装箱的方法和系统。 一种方法包括通过检查系统的光学子系统对于为晶片生成的每个检查图像帧中的每个图像补片进行对准以设计晶片的信息。 该方法还包括在图像斑块中检测到的缺陷位置导出多层设计属性。 另外，该方法包括使用多层设计属性构建决策树。 决策树用于将缺陷分离成对晶片上形成的器件产生不同产量的影响。 该方法还包括使用决策树将缺陷合并。

    Design Based Sampling and Binning for Yield Critical Defects
    5.
    发明申请
    Design Based Sampling and Binning for Yield Critical Defects 有权
    基于设计的采样和分拣产量关键缺陷

    公开(公告)号：US20140307947A1

    公开(公告)日：2014-10-16

    申请号：US14251415

    申请日：2014-04-11

    Applicant: KLA-Tencor Corporation

    Inventor： Satya Kurada ,  Raghav Babulnath ,  Kwok Ng ,  Lisheng Gao

    IPC: G06T7/00

    CPC classification number: G06T7/0006 ,  G01N21/9501 ,  G01N21/956 ,  G01N21/95607 ,  G01N2021/95676 ,  G01N2201/06113 ,  G01N2201/068 ,  G01N2201/10 ,  G01N2201/12 ,  G06K9/00 ,  G06K9/66 ,  G06T7/0008 ,  G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

    Abstract: Methods and systems for design based sampling and binning for yield critical defects are provided. One method includes aligning each image patch in each inspection image frame generated for a wafer by an optical subsystem of an inspection system to design information for the wafer. The method also includes deriving multiple layer design attributes at locations of defects detected in the image patches. In addition, the method includes building a decision tree with the multiple layer design attributes. The decision tree is used to separate the defects into bins with different yield impacts on a device being formed on the wafer. The method also includes binning the defects with the decision tree.

    Abstract translation: 提供了用于产量关键缺陷的基于设计的抽样和装箱的方法和系统。 一种方法包括通过检查系统的光学子系统对于为晶片生成的每个检查图像帧中的每个图像补片进行对准以设计晶片的信息。 该方法还包括在图像斑块中检测到的缺陷位置导出多层设计属性。 另外，该方法包括使用多层设计属性构建决策树。 决策树用于将缺陷分离成对晶片上形成的器件产生不同产量的影响。 该方法还包括使用决策树将缺陷合并。

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