Project for improving brewery process using Artificial Intelligence.
The goal is to ensure a stable quality of the beer over production batches.
Our approach relies on the combination of two types of information:
1. Parameters set by the operator
2. Sensor data, in particular Near Infrared Spectroscopy
Using a deep reinforcement learning approach, our system will suggest optimal parameters to the operator, in particular during the fermentation process.
June 10, 2020
Why NIR helps to control the beer process production?
As reported recently: ‘Near infrared and mid infrared spectroscopy offer opportunities to predict dozens to hundreds of compounds simultaneously at different stages of the brewing process.’ This gives an opportunity to monitor and ensure the stability of the complex wort and beer composition, not just content of specific components. NIR can help at different stages of beer production from …
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We can distinguish three main techniques currently used in machine learning: Supervised learning We input to software a set of examples, which are labelled, therefore we ‘explain’ exactly how they should be interpreted Based on this, some generalised observations about the data can be made By extrapolation, software can ‘explain’ future, unknown data This approach is …