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Tag: machine learning

  • January 17, 2023
  • Miscellaneous

Machine Learning and First Principle Models for Process Optimization

Machine learning and first principle models are two widely discussed approaches for process optimization nowadays. First principle models, which are also referred as dynamic models,......

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  • 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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  • December 6, 2022
  • AI, Applications

Manufacturing needs MVDA: An introduction to modern, scalable multivariate data analysis

Machine learning and first principle models are two widely discussed approaches for process optimization nowadays. First principle models, which are also referred as dynamic models, have long been one...

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  • November 29, 2022
  • Pharma 4.0

The Current Challenges of Life Science Manufacturing Require the Adoption of Modern Solutions

In the last 2 – 3 years, Life Science industry supply chain disruptions highlighted the need for high-performance, distributed manufacturing that can accelerate the delivery......

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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 14, 2021
  • AI, Technology

It’s time to ditch Apache Spark and adopt Dask

This isn’t a comparison between Apache Spark vs. Dask. But if you are interested in that, Dask is humble enough to include that in their......

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