公开(公告)号：US20160123898A1

公开(公告)日：2016-05-05

申请号：US14931226

申请日：2015-11-03

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: G01N21/95

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。

公开(公告)号：US09922269B2

公开(公告)日：2018-03-20

申请号：US15010887

申请日：2016-01-29

Applicant: KLA-Tencor Corporation

Inventor： Sankar Venkataraman ,  Li He ,  John R. Jordan, III ,  Oksen Baris ,  Harsh Sinha

IPC: G06K9/62 ,  G06T7/00 ,  H01L21/66

CPC classification number: G06K9/6254 ,  G06K9/6255 ,  G06K9/6269 ,  G06K9/628 ,  G06K9/6282 ,  G06T7/0004 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148 ,  H01L22/00 ,  H01L22/12 ,  H01L22/20

Abstract: Defect classification includes acquiring one or more images of a specimen including multiple defects, grouping the defects into groups of defect types based on the attributes of the defects, receiving a signal from a user interface device indicative of a first manual classification of a selected number of defects from the groups, generating a classifier based on the first manual classification and the attributes of the defects, classifying, with the classifier, one or more defects not manually classified by the manual classification, identifying the defects classified by the classifier having the lowest confidence level, receiving a signal from the user interface device indicative of an additional manual classification of the defects having the lowest confidence level, determining whether the additional manual classification identifies one or more additional defect types not identified in the first manual classification, and iterating the procedure until no new defect types are found.

公开(公告)号：US09518934B2

公开(公告)日：2016-12-13

申请号：US14931226

申请日：2015-11-03

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: G01N21/00 ,  G01N21/95 ,  G01N21/88 ,  G03F7/20

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。

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。

公开(公告)号：US20160358041A1

公开(公告)日：2016-12-08

申请号：US15010887

申请日：2016-01-29

Applicant: KLA-Tencor Corporation

Inventor： Sankar Venkataraman ,  Li He ,  John R. Jordan, III ,  Oksen Baris ,  Harsh Sinha

IPC: G06K9/62 ,  G06T7/00

CPC classification number: G06K9/6254 ,  G06K9/6255 ,  G06K9/6269 ,  G06K9/628 ,  G06K9/6282 ,  G06T7/0004 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148 ,  H01L22/00 ,  H01L22/12 ,  H01L22/20

Abstract: Defect classification includes acquiring one or more images of a specimen including multiple defects, grouping the defects into groups of defect types based on the attributes of the defects, receiving a signal from a user interface device indicative of a first manual classification of a selected number of defects from the groups, generating a classifier based on the first manual classification and the attributes of the defects, classifying, with the classifier, one or more defects not manually classified by the manual classification, identifying the defects classified by the classifier having the lowest confidence level, receiving a signal from the user interface device indicative of an additional manual classification of the defects having the lowest confidence level, determining whether the additional manual classification identifies one or more additional defect types not identified in the first manual classification, and iterating the procedure until no new defect types are found.

Abstract translation: 缺陷分类包括获取包含多个缺陷的样本的一个或多个图像，基于缺陷的属性将缺陷分组成缺陷类型组;从用户界面装置接收指示所选择数量的缺陷的第一手动分类的信号 根据第一手工分类和缺陷属性生成分类器，用分类器分类一个或多个缺乏手动分类手段分类的缺陷，识别由具有最低置信度的分类器分类的缺陷 从所述用户界面设备接收指示对具有最低置信水平的所述缺陷进行额外手动分类的信号，确定所述附加手动分类是否识别在所述第一手动分类中未识别的一个或多个附加缺陷类型，以及迭代所述程序 直到找不到新的缺陷类型。