Computer-implemented methods for performing one or more defect-related functions
First Claim
1. A computer-implemented method for identifying noise in inspection data, comprising:
- detecting events in sets of inspection data using detection parameters known to detect noise, nuisance events, and real events, wherein the sets of inspection data are generated by different inspections performed on a specimen; and
identifying the events detected in a number of the sets of inspection data that is less than a predetermined number as noise.
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Abstract
Computer-implemented methods for performing one or more defect-related functions are provided. One method for identifying noise in inspection data includes identifying events detected in a number of sets of inspection data that is less than a predetermined number as noise. One method for binning defects includes binning the defects into groups based on defect characteristics and the sets of the inspection data in which the defects were detected. One method for selecting defects for defect analysis includes binning defects into group(s) based on proximity of the defects to each other and spatial signatures formed by the group(s). A different method for selecting defects for defect analysis includes selecting defects having the greatest diversity of defect characteristic(s) for defect analysis. One method includes classifying defects on a specimen using inspection data generated for the specimen combined with defect review data generated for the specimen.
38 Citations
33 Claims
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1. A computer-implemented method for identifying noise in inspection data, comprising:
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detecting events in sets of inspection data using detection parameters known to detect noise, nuisance events, and real events, wherein the sets of inspection data are generated by different inspections performed on a specimen; and
identifying the events detected in a number of the sets of inspection data that is less than a predetermined number as noise. - View Dependent Claims (2, 3, 4)
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5. A computer-implemented method for binning defects, comprising:
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determining characteristics of defects detected in sets of inspection data generated by different inspections performed on a specimen; and
binning the defects into groups based on the characteristics and the sets of the inspection data in which the defects were detected. - View Dependent Claims (6, 7, 8, 9, 10, 11)
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12. A computer-implemented method for selecting defects for defect analysis on an inspection system, comprising:
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binning defects into one or more groups based on proximity of the defects to each other on a specimen and spatial signatures formed by the one or more groups; and
selecting one or more of the defects in at least one of the one or more groups for defect analysis. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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21. A computer-implemented method for selecting defects for defect analysis, comprising:
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determining one or more characteristics of defects detected on a specimen; and
selecting the defects having the greatest diversity of the one or more characteristics for defect analysis.
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22. A computer-implemented method for selecting one or more parameters of a defect review process, comprising:
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determining one or more characteristics of defects selected for defect review; and
selecting one or more parameters of a process for the defect review based on the one or more characteristics such that different types of the defects can be reviewed with one or more different parameters. - View Dependent Claims (23, 24, 25)
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- 26. A computer-implemented method for classifying defects, comprising classifying defects on a specimen using inspection data generated for the specimen combined with defect review data generated for the specimen.
Specification