公开(公告)号：US10670535B2

公开(公告)日：2020-06-02

申请号：US16296132

申请日：2019-03-07

Applicant: KLA-Tencor Corporation

Inventor： Brian Duffy ,  Ajay Gupta ,  Thanh Huy Ha

IPC: G01N21/88 ,  G03F7/20 ,  G01N21/95 ,  G01N23/00 ,  G01N21/956

Abstract: Methods and systems for determining parameter(s) of a metrology process to be performed on a specimen are provided. One system includes one or more computer subsystems configured for automatically generating regions of interest (ROIs) to be measured during a metrology process performed for the specimen with the measurement subsystem based on a design for the specimen. The computer subsystem(s) are also configured for automatically determining parameter(s) of measurement(s) performed in first and second subsets of the ROIs during the metrology process with the measurement subsystem based on portions of the design for the specimen located in the first and second subsets of the ROIs, respectively. The parameter(s) of the measurement(s) performed in the first subset are determined separately and independently of the parameter(s) of the measurement(s) performed in the second subset.

公开(公告)号：US20180341525A1

公开(公告)日：2018-11-29

申请号：US15978626

申请日：2018-05-14

Applicant: KLA-TENCOR CORPORATION

Inventor： Ajay Gupta ,  Sankar Venkataraman ,  Sashi Balasingam ,  Mohan Mahadevan

IPC: G06F9/50 ,  G06F9/48

Abstract: Real-time job distribution software architectures for high bandwidth, hybrid processor computation systems for semiconductor inspection and metrology are disclosed. The imaging processing computer architecture can be scalable by changing the number of CPUs and GPUs to meet computing needs. The architecture is defined using a master node and one or more worker nodes to run image processing jobs in parallel for maximum throughput. The master node can receive input image data from a semiconductor wafer or reticle. Jobs based on the input image data are distributed to one of the worker nodes. Each worker node can include at least one CPU and at least one GPU. The image processing job can contain multiple tasks, and each of the tasks can be assigned to one of the CPU or GPU in the worker node using a worker job manager to process the image.

公开(公告)号：US20180293721A1

公开(公告)日：2018-10-11

申请号：US15896060

申请日：2018-02-14

Applicant: KLA-Tencor Corporation

Inventor： Ajay Gupta ,  Mohan Mahadevan ,  Sankar Venkataraman ,  Hedong Yang ,  Laurent Karsenti ,  Yair Carmon ,  Noga Bullkich ,  Udy Danino

IPC: G06T7/00 ,  G06T7/564 ,  G01N21/95 ,  G01N21/956 ,  G01N21/88

CPC classification number: G06T7/001 ,  G01N21/8851 ,  G01N21/9501 ,  G01N21/956 ,  G01N21/95607 ,  G01N2021/8867 ,  G01N2021/8887 ,  G05B19/41875 ,  G06N20/00 ,  G06T7/564 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148 ,  H01L22/12 ,  H01L22/20

Abstract: Methods and systems for detecting defects in patterns formed on a specimen are provided. One system includes one or more components executed by one or more computer subsystems, and the component(s) include first and second learning based models. The first learning based model generates simulated contours for the patterns based on a design for the specimen, and the simulated contours are expected contours of a defect free version of the patterns in images of the specimen generated by an imaging subsystem. The second learning based model is configured for generating actual contours for the patterns in at least one acquired image of the patterns formed on the specimen. The computer subsystem(s) are configured for comparing the actual contours to the simulated contours and detecting defects in the patterns formed on the specimen based on results of the comparing.

公开(公告)号：US20170309009A1

公开(公告)日：2017-10-26

申请号：US15275726

申请日：2016-09-26

Applicant: KLA-Tencor Corporation

Inventor： Naoshin Haque ,  Allen Park ,  Ajay Gupta

IPC: G06T7/00

CPC classification number: G06T7/0004 ,  G06T2207/10061 ,  G06T2207/30148 ,  H01L22/12 ,  H01L22/20

Abstract: Methods and systems for providing weak pattern (or hotspot) detection and quantification are disclosed. A weak pattern detection and quantification system may include a wafer inspection tool configured to inspect a wafer and detect defects present on the wafer. The system may also include at least one processor in communication with the wafer inspection tool. The at least one processor may be configured to: perform pattern grouping on the detected defects based on design of the wafer; identify regions of interest based on the pattern grouping; identify weak patterns contained in the regions of interest identified, the weak patterns being patterns deviating from the design by an amount greater than a threshold; validate the weak patterns identified; and report the validated weak patterns or facilitate revision of the design of the wafer based on the validated weak patterns.

公开(公告)号：US10395362B2

公开(公告)日：2019-08-27

申请号：US15896060

申请日：2018-02-14

Applicant: KLA-Tencor Corporation

Inventor： Ajay Gupta ,  Mohan Mahadevan ,  Sankar Venkataraman ,  Hedong Yang ,  Laurent Karsenti ,  Yair Carmon ,  Noga Bullkich ,  Udy Danino

IPC: G06T7/00 ,  G06T7/564 ,  G01N21/95 ,  G01N21/88 ,  G01N21/956

Abstract: Methods and systems for detecting defects in patterns formed on a specimen are provided. One system includes one or more components executed by one or more computer subsystems, and the component(s) include first and second learning based models. The first learning based model generates simulated contours for the patterns based on a design for the specimen, and the simulated contours are expected contours of a defect free version of the patterns in images of the specimen generated by an imaging subsystem. The second learning based model is configured for generating actual contours for the patterns in at least one acquired image of the patterns formed on the specimen. The computer subsystem(s) are configured for comparing the actual contours to the simulated contours and detecting defects in the patterns formed on the specimen based on results of the comparing.