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Tag: technology

  • December 6, 2022
  • AI

Bridging the gap between AI and industrial controls

Our paper titled SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments has recently been accepted by NeurIPS 2022, Datasets and Benchmarks Track. In this......

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  • February 2, 2022
  • AI

Bridge the gap between Process Control and Reinforcement Learning with QuarticGym

Modern process control algorithms are the key to the success of industrial automation. The increased efficiency and quality create value that benefits everyone from the......

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  • January 10, 2022
  • Industry

AI-driven Automation: a Stepping Stone to Autonomous Process Control

Our research mission is to bring the best intelligent autonomy to manufacturing. Undoubtedly, AI-driven industrial control is a big part of it. At NeurIPS 2021......

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  • September 11, 2021
  • Industry

Optimizing Continuous Manufacturing Processes

This is a joint work of Benjamin Decardi-Nelson, Jerry Cheng, and Mohan Zhang. The future of manufacturing is continuous and autonomous. Compared to batch manufacturing,......

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  • June 28, 2021
  • AI, Industry, Technology

Optimization with Offline Reinforcement Learning

We showed that when you are early in your digitalization journey where you only have access to manipulated variables (e.g. sugar feed rate) and the outcome (e.g. yield), you......

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  • June 28, 2021
  • AI, Industry, Technology

Optimizing DoE and Production Runs with Little Data

For many batch processes (e.g. in Life Sciences, Food & Beverage), the Design of Experiments (DoE) is usually conducted before scaling up to production...

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  • June 21, 2021
  • AI, Industry, Technology

Open sourcing A better Penicillin Bioreactor Simulation

For industries like Life Sciences, it is challenging to collect a large amount of data with high quality that is needed for machine learning and autonomous control applic...

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