In batch manufacturing, optimizing processes for consistent yields and quality standards remains a top priority. Yet, the intricacies of batch operations often pose challenges in…
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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…
Continue ReadingManufacturing needs MVDA: An introduction to modern, scalable multivariate data analysis
Although there are speed efficiencies that can be achieved by successfully digitizing the enterprise, the competitive advantages will be gained by achieving a new level…
Continue ReadingThe Myth of the Elusive Golden Batch?
The ‘Golden Batch’ is your ideal batch, the one that came out perfectly, the way you intended: the recipe is followed perfectly, and the process…
Continue ReadingBridge 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…
Continue ReadingOptimization 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…
Continue ReadingOptimizing 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 runs. We believe that Bayesian Optimization and its variants could…
Continue ReadingA Taste of Bayesian Optimization – Part 2
In Part 1, we discussed simple Bayesian optimization (BO), and now we further exam BO by taking into account uncontrollable contextual information and constraints. 1….
Continue ReadingA Taste of Bayesian Optimization – Part 1
Bayesian optimization (BO) is a sample-efficient optimization method focused on solving the problem when the objective function f_0 is unknown or expensive to evaluate. At…
Continue ReadingOpen 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 applications. Instead, we settle with simulations where…
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