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公开(公告)号：US20200175664A1
公开(公告)日：2020-06-04
申请号：US16355584
申请日：2019-03-15
Applicant: KLA-Tencor Corporation
Inventor： Soren Konecky , Bjorn Brauer
Abstract: A semiconductor die is inspected using an optical microscope to generate a test image of the semiconductor die. A difference image between the test image of the semiconductor die and a reference image is derived. For each defect of a plurality of defects for the semiconductor die, a point-spread function is fit to the defect as indicated in the difference image and one or more dimensions of the fitted point-spread function are determined. Potential defects of interest in the plurality of defects are distinguished from nuisance defects, based at least in part on the one or more dimensions of the fitted point-spread function for respective defects of the plurality of defects.
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公开(公告)号：US10648925B2
公开(公告)日：2020-05-12
申请号：US15828632
申请日：2017-12-01
Applicant: KLA-Tencor Corporation
Inventor： Eugene Shifrin , Bjorn Brauer , Sumit Sen , Ashok Mathew , Sreeram Chandrasekaran , Lisheng Gao
IPC: G06K9/00 , G01N21/95 , G01N21/956 , H01L21/66
Abstract: Defects from a hot scan can be saved, such as on persistent storage, random access memory, or a split database. The persistent storage can be patch-based virtual inspector virtual analyzer (VIVA) or local storage. Repeater defect detection jobs can determined and the wafer can be inspected based on the repeater defect detection jobs. Repeater defects can be analyzed and corresponding defect records to the repeater defects can be read from the persistent storage. These results may be returned to the high level defect detection controller.
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公开(公告)号：US10402688B2
公开(公告)日：2019-09-03
申请号：US15720272
申请日：2017-09-29
Applicant: KLA-Tencor Corporation
Inventor： Bjorn Brauer , Vijay Ramachandran , Richard Wallingford , Scott Allen Young
Abstract: Systems and methods for providing an augmented input data to a convolutional neural network (CNN) are disclosed. Wafer images are received at a processor. The wafer image is divided into a plurality of references images each associated with a die in the wafer image. Test images are received. A plurality of difference images are created by differences the test images with the reference images. The reference images and difference images are assembled into the augmented input data for the CNN and provided to the CNN.
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公开(公告)号：US10360671B2
公开(公告)日：2019-07-23
申请号：US15646808
申请日：2017-07-11
Applicant: KLA-Tencor Corporation
Inventor： Ravichander Rao , Gary Taan , Andreas Russ , Bjorn Brauer , Roger Davis , Bryant Mantiply , Swati Ramanathan , Karen Biagini
Abstract: Systems and methods for tool health monitoring and matching through integrated real-time data collection, event prioritization, and automated determination of matched states through image analysis are disclosed. Data from the semiconductor production tools can be received in real-time. A control limit impact (CLI) of the parametric data and the defect attributes data can be determined and causation factors can be prioritized. Image analysis techniques can compare images and can be used to judge tool matching, such as by identifying one of the states at which the two or more of the semiconductor manufacturing tools match.
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公开(公告)号：US20180144442A1
公开(公告)日：2018-05-24
申请号：US15797867
申请日：2017-10-30
Applicant: KLA-Tencor Corporation
Inventor： Bjorn Brauer
CPC classification number: G06T5/002 , G06K9/6202 , G06T3/0068 , G06T5/50 , G06T7/001 , G06T2207/20224 , G06T2207/30148
Abstract: Noise reduction in a difference image of an optical inspection tool is provided by calculating a difference image across layers of a multi-layered wafer. A first wafer image of a first wafer layer and a second wafer image of a second wafer layer are used. The first wafer image and the second wafer image are at a same planar location on the multi-layered wafer, but of different layers and/or after different process steps. A first difference image is calculated between the first wafer image and the second wafer image to reduce wafer noise. Defects can be identified using the first difference image. A system with an image data acquisition subsystem can be used to perform this technique.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20180075594A1
公开(公告)日：2018-03-15
申请号：US15371882
申请日：2016-12-07
Applicant: KLA-Tencor Corporation
Inventor： Bjorn Brauer
CPC classification number: G06K9/66 , G01N21/88 , G06K9/6267 , G06T7/001 , G06T2207/20084 , G06T2207/30148
Abstract: Systems and methods for classifying defects using hot scans and convolutional neural networks (CNNs) are disclosed. Primary scanning modes are identified by a processor and a hot scan of a wafer is performed. Defects of interest and nuisance data are selected and images of those areas are captured using one or more secondary scanning modes. Image sets are collected and divided into subsets. CNNs are trained using the image subsets. An ideal secondary scanning mode is determined and a final hot scan is performed. Defects are filtered and classified according to the final hot scan and the ideal secondary scanning mode CNN. Disclosed systems for classifying defects utilize image data acquisition subsystems such as a scanning electron microscope as well as processors and electronic databases.
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公开(公告)号：US20170345142A1
公开(公告)日：2017-11-30
申请号：US15356799
申请日：2016-11-21
Applicant: KLA-Tencor Corporation
Inventor： Bjorn Brauer , Santosh Bhattacharyya
CPC classification number: G06T7/0006 , G06K9/6202 , G06T7/001 , G06T2207/10061 , G06T2207/30148
Abstract: Defect detection is performed by comparing a test image and a reference image with a rendered design image, which may be generated from a design file. This may occur because a comparison of the test image and another reference image was inconclusive due to noise. The results of the two comparisons with the rendered design image can indicate whether a defect is present in the test image.
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公开(公告)号：US10557802B2
公开(公告)日：2020-02-11
申请号：US16101553
申请日：2018-08-13
Applicant: KLA-TENCOR CORPORATION
Inventor： Bjorn Brauer , Hucheng Lee
Abstract: Repeater analysis at a first threshold identifies repeater defects. The repeater defects are located at a coordinate that is the same on each reticle. Images on every reticle of the semiconductor wafer at the coordinate are received, and a plurality of signed difference images are obtained. A repeater threshold for signed difference images is calculated, as is consistency of the polarity. The threshold is applied to the images and a number of defects per each repeater that remain are determined. A secondary repeater threshold can be applied for nuisance filtering.
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公开(公告)号：US20190287232A1
公开(公告)日：2019-09-19
申请号：US16295715
申请日：2019-03-07
Applicant: KLA-TENCOR CORPORATION
Inventor： Bjorn Brauer
IPC: G06T7/00
Abstract: A best optical inspection mode to detect defects can be determined when no defect examples or only a limited number of defect examples are available. A signal for a defect of interest at the plurality of sites and for the plurality of modes can be determined using electromagnetic simulation. A ratio of the signal for the defect of interest to the noise at each combination of the plurality of sites and the plurality of modes can be determined. A mode with optimized signal-to-noise characteristics can be determined based on the ratios.
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公开(公告)号：US20190025229A1
公开(公告)日：2019-01-24
申请号：US15947730
申请日：2018-04-06
Applicant: KLA-Tencor Corporation
Inventor： Bjorn Brauer
IPC: G01N21/95 , G06T7/00 , G01N21/956 , G06F17/50
Abstract: Methods and systems for identifying a source of nuisance defects on a wafer are provided. One method includes detecting defects on a wafer by applying a hot threshold to output generated for the wafer by a detector of an inspection subsystem such that at least a majority of the detected defects include nuisance defects and determining locations of the detected defects with respect to design information for the wafer. In addition, the method includes stacking information for the detected defects based on the determined locations relative to a structure on the wafer such that the detected defects having the same locations relative to the structure are coincident with each other in results of the stacking. The method further includes identifying a source of the nuisance defects based on the results of the stacking.
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