KLA had 39 patents in artificial intelligence during Q4 2023. KLA Corp’s patents in Q4 2023 focus on inspection systems that utilize multiple images taken at different process steps to identify defects in samples. These systems incorporate optical imaging subsystems, controllers, unsupervised and supervised classifiers to generate probabilistic context maps and identify defects of interest (DOIs) on samples. The inspection recipes are developed by generating images with different optical inspection modes and selecting the best combination based on a metric to identify defects on test samples. GlobalData’s report on KLA gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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KLA grant share with artificial intelligence as a theme is 43% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Inspection with previous step subtraction (Patent ID: US20230316478A1)
The patent filed by KLA Corp describes an inspection system that generates images of sample regions before and after a process step, identifies a test region and comparison regions, and generates a multi-step difference image to detect defects in the test region associated with the process step. The system uses a weighted subtraction technique to generate the multi-step difference image, with weights determined by fitting, regression, multi-color adaptive threshold, or machine learning techniques. Defects detected can include deviations in shape, size, or orientation, absence of intended features, scratches, pits, residual material, unintended bridges, or breaks in features.
The inspection system and method outlined in the patent involve receiving and processing images of sample regions before and after a process step to identify defects associated with the process. The system utilizes a combination of first-step and second-step images to generate a multi-step difference image, with the number of images used and weights for subtraction determined by various techniques. Defect detection can be classified as nuisance or of interest, and the system can utilize machine learning algorithms or adaptive threshold techniques for defect identification. The patent also covers different imaging sub-system configurations, such as bright-field or dark-field, to capture the necessary images for defect analysis.
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