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Machine learning

Patent Application for Reinforcement Learning in Substrate Processing Facilities Released

Strategic Insights

— 1 min read

Researchers Prafulla Nath Dawadi, David Everton Norman, and Harel Moshe Yedidsion have filed a patent application for a method utilizing reinforcement learning to optimize substrate processing in facilities. The invention aims to maximize processing on higher-yield tools while meeting production thresholds. Key components include identifying current state data, providing it to a trained reinforcement learning agent, and receiving output parameters to optimize processing. The system also encompasses identifying reward data and training the reinforcement learning agent to optimize processing. The patent application provides a comprehensive outline of the method, including claims, methods, and a non-transitory computer-readable medium.

Key Takeaways:

  • The patent application details a method for optimizing substrate processing in facilities using reinforcement learning.
  • The invention identifies current state data associated with substrate processing facilities and provides it to a trained reinforcement learning agent.
  • The trained reinforcement learning agent receives output associated with parameters to optimize processing, including maximizing lot processing on higher-yield tools while meeting production thresholds.
  • The system also includes training a reinforcement learning agent using state and reward data to generate a trained reinforcement learning agent.
  • The patent application outlines specific claims, methods, and a non-transitory computer-readable medium for implementing the invention.
  • The supported inventors include Prafulla Nath Dawadi, David Everton Norman, and Harel Moshe Yedidsion.

Statistics:

  • The patent application was filed on July 24, 2024, and released on October 16, 2025.
  • The invention aims to optimize substrate processing in facilities, with a focus on higher-yield tools and production thresholds.
  • The patent application includes 20 claims, detailing specific aspects of the method.
  • The supported inventors are based in San Mateo, CA, Bountiful, UT, and Pflugerville, TX.

Sources:

  • Dawadi, P. et al. (2024). Reinforcement Learning For Substrate Processing Facility. U.S. Patent Application Number 20250321548.
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