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11. 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。

12. 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。

13. 发明申请

US20120271587A1 EQUIPMENT STATUS MONITORING METHOD, MONITORING SYSTEM, AND MONITORING PROGRAM 审中-公开
标题翻译：设备状态监测方法，监测系统和监测方案
公开(公告)号：US20120271587A1
公开(公告)日：2012-10-25
申请号：US13500932
申请日：2010-06-16
申请人： Hisae Shibuya , Shunji Maeda
发明人： Hisae Shibuya , Shunji Maeda
IPC分类号： G06F15/00
CPC分类号： G05B23/0229
摘要： Anomaly sign detection methods such as those found in plants cannot detect anomalies when relevant sensor information is not acquired, and while it is possible to detect anomalies through changes in sensor output when manual operations are performed, it is difficult to distinguish between anomalies such as those caused only by the sensor signal and actual anomalies which should be detected. The disclosed method uses event signals, which contain a signal based on the status of a unit unable to acquire sensor information and a signal based on human operations. An event sequence is extracted from an event signal outputted from a piece of equipment and grouped by clustering, then a frequency matrix is created for the alarms generated within a prescribed interval of an event sequence, and a prediction of alarms with a high probability of occurring for an event sequence is output on the basis of the frequency matrix.
摘要翻译：异常符号检测方法如植物中发现的检测方法无法检测到相关传感器信息未获得的异常现象，而通过执行手动操作时传感器输出的变化可以检测到异常，则很难区分异常仅由传感器信号和应检测的实际异常引起。所公开的方法使用事件信号，其包含基于不能获取传感器信息的单元的状态的信号和基于人类操作的信号。从从一件设备输出的事件信号中提取事件序列并通过聚类分组，然后为在事件序列的规定间隔内产生的报警创建频率矩阵，并且以高概率发生的报警的预测基于频率矩阵输出事件序列。

14. 发明申请

US20110228262A1 APPARATUS OF INSPECTING DEFECT IN SEMICONDUCTOR AND METHOD OF THE SAME 失效
标题翻译：检查半导体缺陷的设备及其方法
公开(公告)号：US20110228262A1
公开(公告)日：2011-09-22
申请号：US13116466
申请日：2011-05-26
申请人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
发明人： Akira Hamamatsu , Shunji Maeda , Hisae Shibuya
IPC分类号： G01N21/00
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。

15. 发明申请

US20110191076A1 ERROR DETECTION METHOD AND SYSTEM 有权
标题翻译：错误检测方法与系统
公开(公告)号：US20110191076A1
公开(公告)日：2011-08-04
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： G06F17/10
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）和运行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。

16. 发明授权

US07848563B2 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：US07848563B2
公开(公告)日：2010-12-07
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： G06K9/62 , G06K9/36
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。

17. 发明申请

US20090290168A1 Inspecting Method and Inspecting Apparatus for Substrate Surface 有权
标题翻译：基板表面检查方法及检查装置
公开(公告)号：US20090290168A1
公开(公告)日：2009-11-26
申请号：US12470505
申请日：2009-05-22
申请人： Akira HAMAMATSU , Yoshimasa Oshima , Shunji Maeda , Hisae Shibuya , Yuta Urano , Toshiuki Nakao , Shigenobu Maruyama
发明人： Akira HAMAMATSU , Yoshimasa Oshima , Shunji Maeda , Hisae Shibuya , Yuta Urano , Toshiuki Nakao , Shigenobu Maruyama
IPC分类号： G01B11/30 , G01B11/06
CPC分类号： G01B11/303 , G01N21/47 , G01N21/94 , G01N21/9501
摘要： To inspect a substrate such as a semiconductor substrate for surface roughness at high precision.The surface roughness of the substrate is measured in each frequency band of the surface roughness by applying a light to the substrate surface and detecting a scattered light or reflected light at a plurality of azimuth or elevation angles.
摘要翻译：以高精度检查用于表面粗糙度的半导体基板等基板。通过向基板表面施加光并以多个方位角或仰角检测散射光或反射光，测量表面粗糙度的每个频带中的基板的表面粗糙度。

18. 发明授权

US07474394B2 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：US07474394B2
公开(公告)日：2009-01-06
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。

19. 发明授权

US09659250B2 Facility state monitoring method and device for same 有权
公开(公告)号：US09659250B2
公开(公告)日：2017-05-23
申请号：US14241780
申请日：2011-08-31
申请人： Hisae Shibuya , Shunji Maeda
发明人： Hisae Shibuya , Shunji Maeda
IPC分类号： G06N5/00 , G06F1/00 , G06N5/02 , G05B23/02 , G06N99/00
CPC分类号： G06N5/02 , G05B23/0221 , G05B23/0254 , G05B2219/32201 , G06N99/005 , Y02P90/22
摘要： In case-based anomaly indication detection in a facility, there are problems such as error generation due to insufficient learning data or execution difficulty due to increased memory capacity and calculation time when the learning data period has been increased to obtain the learning data sufficiently. Provided is a method for monitoring facility state on the basis of a time series signal outputted from the facility, wherein an operation pattern label for each fixed interval is assigned on the basis of the time series signal, learning data is selected on the basis of the operation pattern label for each fixed interval, a normal model is created on the basis of the selected learning data, an anomaly measure is calculated on the basis of the time series signal and the normal model, and the facility state is determined to be anomaly or normal on the basis of the calculated anomaly measure.

20. 发明授权

US08682824B2 Method and device for monitoring the state of a facility 有权
标题翻译：监控设施状态的方法和装置
公开(公告)号：US08682824B2
公开(公告)日：2014-03-25
申请号：US13383841
申请日：2010-07-28
申请人： Hisae Shibuya , Shunji Maeda
发明人： Hisae Shibuya , Shunji Maeda
IPC分类号： G06N5/00
CPC分类号： G05B23/021 , G06N99/005
摘要： This invention provides method for detecting advance signs of anomalies, event signals outputted from the facility are used to create a separate mode for each operating state, a normal model is created for each mode, the sufficiency of learning data for each mode is checked, a threshold is set according to the results of said check, and anomaly identification is performed using said threshold. Also, for diagnosis, a frequency matrix is created in advance, with result events on the horizontal axis and cause events on the vertical axis, and the frequency matrix is used to predict malfunctions. Malfunction events are inputted as result events, and quantized sensor signals having anomaly measures over the threshold are inputted as cause events.
摘要翻译：本发明提供了用于检测异常的提前符号的方法，从设施输出的事件信号用于为每个操作状态创建单独的模式，为每个模式创建正常模型，检查每种模式的学习数据的充分性，根据所述检查的结果设定阈值，使用所述阈值进行异常识别。另外，为了进行诊断，预先创建频率矩阵，结果事件在水平轴上，导致垂直轴上的事件，频率矩阵用于预测故障。作为结果事件输入故障事件，并且将具有超过阈值的异常测量的量化的传感器信号作为原因事件输入。

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