ASML Holding has been granted a patent for a method that analyzes manufacturing processes. The method involves obtaining a multi-dimensional probability density function of process parameters, mapping it to a performance probability function, and using this information to control or configure the manufacturing process. GlobalData’s report on ASML Holding 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 ASML Holding, AI-assisted photolithography was a key innovation area identified from patents. ASML Holding's grant share as of June 2024 was 56%. Grant share is based on the ratio of number of grants to total number of patents.
Method for analyzing and controlling manufacturing process performance
The patent US12044980B2 outlines a method for optimizing manufacturing processes through the use of a multi-dimensional probability density function (PDF) and a performance function. The method involves obtaining a PDF that represents the expected distribution of various process parameters, such as focus, dose, and overlay in lithographic processes, or RF power and substrate temperature in other manufacturing contexts. A hardware computer utilizes the performance function to map this PDF to a performance probability function, which is then used to control or configure the manufacturing process. This approach allows for real-time adjustments based on the performance probability function, enhancing the efficiency and effectiveness of the manufacturing operations.
Additionally, the patent describes the potential for machine learning algorithms to be employed in obtaining the multi-dimensional PDF, as well as the ability to analyze the performance probability function to identify optimal ranges for process parameters. The method also includes steps for calibrating process windows and selecting process settings based on identified parameter ranges. The computer program product associated with the patent contains instructions for executing these methods, enabling automated control and configuration of manufacturing processes to improve yield and performance metrics such as edge placement error and critical dimension uniformity. Overall, this patent presents a systematic approach to leveraging statistical modeling and computational techniques in manufacturing optimization.
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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.
