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21. 发明授权

US07751036B2 Apparatus of inspecting defect in semiconductor and method of the same 失效
标题翻译：检测半导体缺陷的装置及其方法
公开(公告)号：US07751036B2
公开(公告)日：2010-07-06
申请号：US12349373
申请日：2009-01-06
申请人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
发明人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
IPC分类号： G01N21/88
CPC分类号： G01N21/956
摘要： When size of a defect on an increasingly miniaturized pattern is obtained by defect inspection apparatus in the related art, a value is inconveniently given, which is different from a measured value of the same defect by SEM. Thus, a dimension value of a defect detected by defect inspection apparatus needs to be accurately calculated to be approximated to a value measured by SEM. To this end, size of the defect detected by the defect inspection apparatus is corrected depending on feature quantity or type of the defect, thereby defect size can be accurately calculated.
摘要翻译：当通过现有技术的缺陷检查装置获得越来越小型化的图案的缺陷的尺寸时，不方便地给出不同于SEM的相同缺陷的测量值的值。因此，需要精确地计算由缺陷检查装置检测到的缺陷的尺寸值，以近似于通过SEM测量的值。为此，由缺陷检查装置检测到的缺陷的尺寸根据缺陷的特征量或类型进行修正，从而可以精确地计算缺陷尺寸。

22. 发明申请

US20080075352A1 DEFECT CLASSIFICATION METHOD AND APPARATUS, AND DEFECT INSPECTION APPARATUS 有权
标题翻译：缺陷分类方法和装置，以及缺陷检查装置
公开(公告)号：US20080075352A1
公开(公告)日：2008-03-27
申请号：US11779905
申请日：2007-07-19
申请人： HISAE SHIBUYA , Shunji Maeda , Akira Hamamatsu
发明人： HISAE SHIBUYA , Shunji Maeda , Akira Hamamatsu
IPC分类号： G06K9/00
CPC分类号： G06T7/0004 , G01N21/9501 , G01N21/956 , G06K9/03 , G06K9/6254 , G06K9/6282 , G06T2207/30148
摘要： A defect classification method to classify defects by using a classifier having a binary tree structure based on features of defects extracted from detected signals acquired from a defect inspection apparatus includes a classifier construction process for constructing the classifier by setting a branch condition including defect classes respectively belonging to groups located on both sides of the branch point, a feature to be used for branching, and a discriminant reference, for each branch point in the structure based on instruction of defect classes and feature data respectively associated therewith beforehand. The process includes a priority order specification process for previously specifying target classification performance of purity and accuracy for each defect class, whole and in worst case, with priority order, and an evaluation process for evaluating whether the specified target classification performance under the branching condition is satisfied and displaying a result of evaluation, every item.
摘要翻译：通过使用基于从缺陷检查装置获取的检测信号提取的缺陷的特征的具有二叉树结构的分类器对缺陷进行分类的缺陷分类方法包括：分类器构造处理，用于通过设置包括分别属于的缺陷类的分支条件来构建分类器基于分支点两侧的组，用于分支的特征，以及基于与预先分别相关联的缺陷类别和特征数据的指示的结构中的每个分支点的判别参考。该处理包括优先顺序指定处理，用于以优先级顺序预先指定每个缺陷类的全部和最坏情况下的纯度和精度的目标分类性能，以及用于评估分支条件下的指定目标分类性能是否为满意并显示评估结果，每个项目。

23. 发明申请

US20070019185A1 Apparatus of inspecting defect in semiconductor and method of the same 有权
标题翻译：检测半导体缺陷的装置及其方法
公开(公告)号：US20070019185A1
公开(公告)日：2007-01-25
申请号：US11488622
申请日：2006-07-19
申请人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
发明人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
IPC分类号： G01N21/88
CPC分类号： G01N21/956
摘要： When size of a defect on an increasingly miniaturized pattern is obtained by defect inspection apparatus in the related art, a value is inconveniently given, which is different from a measured value of the same defect by SEM. Thus, a dimension value of a defect detected by defect inspection apparatus needs to be accurately calculated to be approximated to a value measured by SEM. To this end, size of the defect detected by the defect inspection apparatus is corrected depending on feature quantity or type of the defect, thereby defect size can be accurately calculated.
摘要翻译：当通过现有技术的缺陷检查装置获得越来越小型化的图案的缺陷的尺寸时，不方便地给出不同于SEM的相同缺陷的测量值的值。因此，需要精确地计算由缺陷检查装置检测到的缺陷的尺寸值，以近似于通过SEM测量的值。为此，由缺陷检查装置检测到的缺陷的尺寸根据缺陷的特征量或类型进行修正，从而可以精确地计算缺陷尺寸。

24. 发明授权

US08630962B2 Error detection method and its system for early detection of errors in a planar or facilities 有权
标题翻译：错误检测方法及其系统，用于早期检测平面或设施中的错误
公开(公告)号：US08630962B2
公开(公告)日：2014-01-14
申请号：US13057831
申请日：2009-05-29
申请人： Shunji Maeda , Hisae Shibuya
发明人： Shunji Maeda , Hisae Shibuya
IPC分类号： G06F15/18
CPC分类号： G05B23/0254 , G06K9/00536 , G06K9/6252 , G06K9/6272 , G06K9/6284
摘要： Provided are a method which permits complete training data and data with added errors, and enables the early and accurate discovery of errors in facilities such as a plant, and a system thereof. To achieve the objectives, (1) the behavior of temporal data is observed over time, and the trace is divided into clusters; (2) the divided cluster groups are modeled in sub spaces, and the discrepancy values are calculated as errors candidates; (3) the training data are used (compare, reference, etc.) for reference to determine the state transitions caused by the changes over time, the environmental changes, the maintenance (parts replacement), and the operation states; and (4) the modeling is a sub space method such as regression analysis or projection distance method of every N data removing N data items, (N=0, 1, 2, . . . ) (for example, when N=1, one error data item is considered to have been added, this data is removed, then the modeling is performed), or a local sub space method. Linear fitting in regression analysis is equivalent to the lowest order regression analysis.
摘要翻译：提供了一种允许完整的训练数据和具有附加错误的数据的方法，并且能够及早准确地发现诸如工厂及其系统之类的设施中的错误。为了实现目标，（1）随时间观察时间数据的行为，并将踪迹分为簇; （2）划分的群集组在子空间中建模，差异值计算为错误候选; （3）使用训练数据（比较，参考等）作为参考，确定随时间变化，环境变化，维护（部件更换）和操作状态引起的状态转换; （4）建模是N次数据去除N个数据项（N = 0,1,2，...）的回归分析或投影距离法的子空间法（例如，当N = 1时，一个错误数据项被认为已被添加，该数据被删除，然后进行建模）或本地子空间方法。回归分析中的线性拟合等价于最低阶回归分析。

25. 发明申请

US20060159330A1 Method and apparatus for inspecting a defect of a pattern 有权
标题翻译：检查图案缺陷的方法和装置
公开(公告)号：US20060159330A1
公开(公告)日：2006-07-20
申请号：US11328231
申请日：2006-01-10
申请人： Kaoru Sakai , Shunji Maeda , Hisae Shibuya , Hidetoshi Nishiyama
发明人： Kaoru Sakai , Shunji Maeda , Hisae Shibuya , Hidetoshi Nishiyama
IPC分类号： G06K9/00
CPC分类号： G06T7/0004 , G06T7/001 , G06T2207/30148
摘要： In a pattern inspection apparatus, influences of pattern brightness variations that is caused in association with, for example, a film thickness difference or a pattern width variation can be reduced, high sensitive pattern inspection can be implemented, and a variety of defects can be detected. Thereby, the pattern inspection apparatus adaptable to a broad range of processing steps is realized. In order to realize this, the pattern inspection apparatus of the present invention performs comparison between images of regions corresponding to patterns formed to be same patterns, thereby determining mismatch portions across the images to be defects. The apparatus includes multiple sensors capable of synchronously acquiring images of shiftable multiple detection systems different from one another, and an image comparator section corresponding thereto. In addition, the apparatus includes means of detecting a statistical offset value from the feature amount to be a defect, thereby enabling the defect to be properly detected even when a brightness difference is occurring in association with film a thickness difference in a wafer.
摘要翻译：在图案检查装置中，可以减少与膜厚差或图案宽度变化相关联引起的图案亮度变化的影响，可以实现高灵敏度图案检查，并且可以检测各种缺陷。由此，可以实现适应于广泛的处理步骤的图案检查装置。为了实现这一点，本发明的图案检查装置对与形成为相同图案的图案相对应的区域的图像进行比较，从而确定跨越图像的不匹配部分是缺陷。该装置包括能够同时获取彼此不同的可移动多个检测系统的图像的多个传感器，以及与其对应的图像比较部。此外，该装置包括检测从特征量成为缺陷的统计偏移值的装置，从而即使当与膜中的厚度差相关联地发生亮度差时，也能够适当地检测缺陷。

26. 发明授权

US08620061B2 Visual inspection method and apparatus and image analysis system 有权
标题翻译：目视检查方法及装置及图像分析系统
公开(公告)号：US08620061B2
公开(公告)日：2013-12-31
申请号：US13405444
申请日：2012-02-27
申请人： Hisae Shibuya , Shunji Maeda
发明人： Hisae Shibuya , Shunji Maeda
IPC分类号： G06K9/00
CPC分类号： G06T7/0004 , G06T2207/30148
摘要： A visual inspection method and apparatus detecting a defect with the use of a detected signal obtained by illuminating one of a light and an electron beam onto a substrate to be inspected. The visual inspection method and apparatus includes calculation of an image feature based on an image of the detected defect, calculation of a coordinate feature based on position information of the detected defect, and outputting of real defect information by performing false alarm judgment by processing with respect to one of the image feature and the coordinate feature.
摘要翻译：使用通过将光和电子束中的一个照射到待检查的基板上获得的检测信号来检测缺陷的目视检查方法和装置。目视检查方法和装置包括基于检测到的缺陷的图像计算图像特征，基于检测到的缺陷的位置信息来计算坐标特征，并且通过以下方式进行伪报警判断来输出实际缺陷信息：到一个图像特征和坐标特征。

27. 发明申请

US20130173218A1 Malfunction Detection Method and System Thereof 审中-公开
标题翻译：故障检测方法及其系统
公开(公告)号：US20130173218A1
公开(公告)日：2013-07-04
申请号：US13702531
申请日：2011-05-16
申请人： Shunji Maeda , Hisae Shibuya
发明人： Shunji Maeda , Hisae Shibuya
IPC分类号： G06F17/00
CPC分类号： G06F17/00 , G05B23/0221 , G05B23/0224 , G06Q10/20
摘要： To allow early sensing of anomalies in a manufacturing plant or other infrastructure (plant), provided is a method that acquires data of runtime status of said plant from a plurality of sensors of said plant, makes a model from training data that corresponds to the regular runtime status of said plant, employs the training data thus modeled in computing a anomaly measure of the data acquired from the sensors, and detects anomalies. In computing the anomaly measure, the anomaly is detected by recursively carrying out: a derivation of a residual error from the training data thus modeled acquired from the plurality of sensors, a removal of a signal having a residual error that is greater than a predetermined value, and a computation of the anomaly measure for the data that is acquired from the plurality of sensors whereupon the signal having the large residual error is removed.
摘要翻译：为了允许早期感测制造工厂或其他基础设施（工厂）中的异常，提供了一种从所述设备的多个传感器获取所述设备的运行时状态的数据的方法，从对应于规则的训练数据所述工厂的运行状态采用如下建模的训练数据来计算从传感器获得的数据的异常测量，并检测异常。在计算异常测量时，通过递归地执行：从由多个传感器获取的建模的训练数据中导出残差，去除具有大于预定值的残差的信号，以及从多个传感器获得的数据的异常测量的计算，因此除去具有大残留误差的信号。

28. 发明授权

US08467594B2 Method and apparatus for inspecting patterns formed on a substrate 有权
标题翻译：用于检查在基板上形成的图案的方法和装置
公开(公告)号：US08467594B2
公开(公告)日：2013-06-18
申请号：US12960578
申请日：2010-12-06
申请人： Kaoru Sakai , Shunji Maeda , Hisae Shibuya , Hidetoshi Nishiyama
发明人： Kaoru Sakai , Shunji Maeda , Hisae Shibuya , Hidetoshi Nishiyama
IPC分类号： G06K9/00 , G06K9/68
CPC分类号： G06T7/0004 , G06T7/001 , G06T2207/30148
摘要： In a pattern inspection apparatus, influences of pattern brightness variations that is caused in association with, for example, a film thickness difference or a pattern width variation can be reduced, high sensitive pattern inspection can be implemented, and a variety of defects can be detected. Thereby, the pattern inspection apparatus adaptable to a broad range of processing steps is realized. In order to realize this, the pattern inspection apparatus of the present invention performs comparison between images of regions corresponding to patterns formed to be same patterns, thereby determining mismatch portions across the images to be defects. The apparatus includes multiple sensors capable of synchronously acquiring images of shiftable multiple detection systems different from one another, and an image comparator section corresponding thereto. In addition, the apparatus includes means of detecting a statistical offset value from the feature amount to be a defect, thereby enabling the defect to be properly detected even when a brightness difference is occurring in association with film a thickness difference in a wafer.
摘要翻译：在图案检查装置中，可以减少与膜厚差或图案宽度变化相关联引起的图案亮度变化的影响，可以实现高灵敏度图案检查，并且可以检测各种缺陷。由此，可以实现适应于广泛的处理步骤的图案检查装置。为了实现这一点，本发明的图案检查装置对与形成为相同图案的图案相对应的区域的图像进行比较，从而确定跨越图像的不匹配部分是缺陷。该装置包括能够同时获取彼此不同的可移动多个检测系统的图像的多个传感器，以及与其对应的图像比较部。此外，该装置包括检测从特征量成为缺陷的统计偏移值的装置，从而即使当与膜中的厚度差相关联地发生亮度差时，也能够适当地检测缺陷。

29. 发明申请

US20130073260A1 METHOD FOR ANOMALY DETECTION/DIAGNOSIS, SYSTEM FOR ANOMALY DETECTION/DIAGNOSIS, AND PROGRAM FOR ANOMALY DETECTION/DIAGNOSIS 审中-公开
标题翻译：用于异常检测/诊断的方法，用于异常检测/诊断的系统和用于异常检测/诊断的程序
公开(公告)号：US20130073260A1
公开(公告)日：2013-03-21
申请号：US13641886
申请日：2011-04-05
申请人： Shunji Maeda , Hisae Shibuya , Hiroyuki Magara
发明人： Shunji Maeda , Hisae Shibuya , Hiroyuki Magara
IPC分类号： G06F15/00
CPC分类号： G06F15/00 , G05B23/0224 , G06Q10/06
摘要： In order to provide a method and system for anomaly detection/diagnosis that can detect anomalies quickly and with high sensitivity in a machinery such as a plant, in the present disclosures, sets of maintenance record information comprising operational records, replacement part information and other past cases are associated with each other on a keyword basis, anomalies are detected on the basis of anomaly detection that targets the output signal of a multidimensional sensor attached to the machinery, and by means of connecting the detected anomaly with the associated maintenance record information, the required diagnosis/measures with respect to the anomaly that has arisen are elucidated.
摘要翻译：为了提供一种用于异常检测/诊断的方法和系统，其可以在诸如工厂的机械中快速且高灵敏度地检测异常，在本公开中，包括操作记录，替换部件信息和其他过去的维护记录信息情况在关键字的基础上相互关联，基于针对附接到机器的多维传感器的输出信号的异常检测来检测异常，并且通过将检测到的异常与相关联的维护记录信息相连，阐明了所出现的异常情况所需的诊断/措施。

30. 发明申请

US20120316835A1 ANOMALY DETECTION METHOD AND ANOMALY DETECTION SYSTEM 审中-公开
标题翻译：异常检测方法和异常检测系统
公开(公告)号：US20120316835A1
公开(公告)日：2012-12-13
申请号：US13521767
申请日：2010-12-16
申请人： Shunji Maeda , Hisae Shibuya
发明人： Shunji Maeda , Hisae Shibuya
IPC分类号： G06F15/00
CPC分类号： G05B23/0232 , G01D3/08 , G06K9/00536 , G06K9/6252
摘要： A method and system for detecting an anomaly or a fault in equipment such as a plant. A method of representing the state of the equipment is offered. Output signals from multidimensional sensors are treated as subjects. (1) Normal learning data is created. (2) An anomaly measurement is calculated by a subspace classifier or other method. (3) Trajectories of motions of observational data and learning data are evaluated and their errors are calculated by a linear prediction method or the like. (4) The state of the equipment is represented using the anomaly measurement and the trajectories of the motions. (5) A decision is made regarding an anomaly. A case-based reasoning anomaly detection consists of modeling the learning data by the subspace classifier and detecting candidate anomalies based on the distance relationship between the observational data and the subspace. The trajectories of the motions are based on modeling using a linear prediction method.
摘要翻译：一种用于检测设备等异常或故障的方法和系统。提供了一种表示设备状态的方法。来自多维传感器的输出信号被视为主体。（1）创建正常学习数据。（2）通过子空间分类器或其他方法计算异常测量。（3）评估观测数据和学习数据的运动轨迹，并通过线性预测方法等计算其误差。（4）使用异常测量和运动轨迹表示设备的状态。（5）作出关于异常的决定。基于案例的推理异常检测包括通过子空间分类器对学习数据进行建模，并根据观测数据与子空间之间的距离关系检测候选异常。运动的轨迹基于使用线性预测方法的建模。

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