Statistical learning-based mode selection for multi-mode inspection

• Main Authors: Brauer, Bjorn, Gaind, Vaibhav
• Format: Patent
• Language: English
• Published: 16.08.2022
• Subjects: APPARATUS SPECIALLY ADAPTED THEREFOR; BASIC ELECTRIC ELEMENTS; CALCULATING; CINEMATOGRAPHY; COMPUTING; COUNTING; ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR; ELECTRICITY; ELECTROGRAPHY; HOLOGRAPHY; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MATERIALS THEREFOR; MEASURING; ORIGINALS THEREFOR; PHOTOGRAPHY; PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES,e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTORDEVICES; PHYSICS; SEMICONDUCTOR DEVICES; TESTING

Methods and systems for selecting mode(s) for inspection of specimens are provided. One method includes statistically predicting if data points in a set correspond to defects or nuisances on a specimen. The data points include attribute(s) determined for discrete locations on the specimen from output generated by two or more modes of an inspection system. Events have been detected at the discrete locations with at least one of the modes. The method also includes determining a quantitative measure for each of two or more different combinations of the modes thereby determining different quantitative measures. The quantitative measure for each of the different combinations is responsive to how well one of the combinations detects the defects and minimizes detection of the nuisances. The method further includes selecting one or more of the modes for inspection of specimens of the same type as the specimen based on the determined quantitative measures.