KLA had 43 patents in artificial intelligence during Q1 2024. KLA Corp’s patents in Q1 2024 focus on innovative methods and systems for semiconductor applications. These include deep learning alignment for precise alignment of design information to images on specimens, wafer shape metrology for stress-free shape measurements and overlay prediction, estimating parameters from X-ray scatterometry measurements using machine learning, mask design repair through simulation-based models, and compensating systematic errors across metrology systems using a trained error evaluation model. These patents aim to improve accuracy, efficiency, and performance in semiconductor manufacturing processes. 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 grant share with artificial intelligence as a theme is 48% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Deep learning model-based alignment for semiconductor applications (Patent ID: US20240095935A1)
The patent filed by KLA Corp. describes methods and systems for deep learning alignment in semiconductor applications. The system involves transforming design information for an alignment target into a predicted image using a deep learning model, aligning this predicted image with an image of the alignment target on the specimen, determining the offset between the two images, and storing this offset for use in subsequent processes on the specimen with the imaging subsystem. The deep learning model can be configured as a variational autoencoder and can handle grayscale design images, information for multiple layers of a design, and re-training for different specimens.
The system and method outlined in the patent aim to improve alignment accuracy and efficiency in semiconductor processes by utilizing deep learning models to predict and adjust offsets between design information and actual images on specimens. By incorporating features like grayscale design images, multi-layer design information, and iterative training for different specimens, the system enhances the alignment process for semiconductor applications. Additionally, the patent details the use of runtime-to-design offsets, defect detection methods, and clustering techniques for multiple alignment targets to further optimize the alignment process in semiconductor manufacturing.
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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.
