Tokyo Electron had one patents in big data during Q2 2024. The patent filed by Tokyo Electron Ltd in Q2 2024 involves a storage system that stores model data related to substrate processing conditions, movable part attitudes, and processing results. A processing controller then uses this data to control substrate processing, adjusting conditions and part attitudes to achieve desired processing results. GlobalData’s report on Tokyo Electron gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Tokyo Electron had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Substrate processing apparatus, model data generation apparatus, substrate processing method, and model data generation method (Patent ID: US20240194507A1)
The patent filed by Tokyo Electron Ltd. describes a substrate processing apparatus and method that utilize model data stored in a storage medium to control substrate processing. The model data includes information on processing conditions, the attitude of movable parts affecting processing results, and the desired processing results. The processing circuitry uses this data to adjust processing conditions and movable part attitudes to meet specific processing result requirements. The model data can be generated based on changing parameters and processing results, and can be used to determine values of parameters to achieve desired processing outcomes.
Additionally, the patent describes a model data generation apparatus and method that involve storing data related to substrate processing conditions, movable part attitudes, and processing results in patterns. This data is then used to generate model data that helps derive processing conditions and movable part attitudes based on desired processing outcomes. The model data can be generated through machine learning or by using a physical model of the substrate processing as a constraint. Overall, the patent focuses on utilizing stored model data to optimize substrate processing by controlling various parameters based on specific processing result requirements.
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