KLA had 48 patents in artificial intelligence during Q2 2024. KLA Corp’s patents in Q2 2024 focus on systems and methods for enhancing defect detection and characterization in optical systems using machine learning techniques. These patents include systems for training machine learning-based characterization libraries, detecting defects on specimens using multiple mode images, enhancing defect detection using digital filters and machine learning classifiers, measuring structural parameters based on changes in properties, and estimating overlay offsets between structures on semiconductor wafers using machine learning models. GlobalData’s report on KLA gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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KLA had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: System and method for estimating measurement uncertainty for characterization systems (Patent ID: US20240201637A1)
The patent filed by KLA Corp describes a characterization system that includes controllers with processors executing program instructions to train a machine learning-based library, generate characterization measurements, determine additional measurements using non-machine learning techniques, and compare them to monitor measurement uncertainty. The system aims to improve accuracy by adjusting the machine learning library based on comparisons and includes specific applications like overlay and angular tilt metrology.
The system also involves a method for training the machine learning library, generating measurements, determining additional measurements using non-machine learning techniques, and comparing them to monitor measurement uncertainty. The method includes adjusting the library based on comparisons and specific processes like calculating asymmetry signals and determining overlay functions. This approach enhances the accuracy and reliability of the characterization system, particularly in overlay and angular tilt measurements, by incorporating machine learning and non-machine learning techniques for comprehensive analysis and monitoring of measurement uncertainty.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
