PDF Solutions. has been granted a patent for a computer-implemented method that classifies wafers in semiconductor fabrication. The process involves initial and predicted classifications using rule-based and machine learning models, with user input for final classification, enhancing continuous learning and accuracy in wafer classification. GlobalData’s report on PDF Solutions gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on PDF Solutions, CMOS gate array designing was a key innovation area identified from patents. PDF Solutions's grant share as of June 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.
Wafer classification using collaborative machine learning and user input
The granted patent US12038802B2 outlines a computer-implemented method for classifying wafers during semiconductor fabrication. The method involves displaying wafer identification information on a graphical user interface (GUI) and determining an initial classification for a selected wafer using a rule-based classification model. A predicted classification is then generated through a machine learning model that incorporates both the initial classification and user input. The GUI allows users to interactively update classifications and enter their own classifications, ultimately establishing a final classification. The method also includes saving the various classifications for future reference and training the machine learning model based on the collected data.
Additionally, the patent describes features that enhance user interaction and data retrieval. Users can confirm or modify classifications, and the GUI provides options to drill down into detailed wafer information. The method allows for feedback from multiple users, which can help resolve classification conflicts by incorporating additional information, such as the timing of user feedback. The system is designed to periodically retrain the machine learning model based on user interactions and classifications, ensuring continuous improvement in the classification process. Overall, the patent presents a comprehensive approach to wafer classification that integrates rule-based and machine learning techniques, facilitating user engagement and data-driven decision-making in semiconductor fabrication.
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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.
