Speaker
Daniel Palací-López
(IFF Benicarló )
Description
Machine Learning is now part of many university curriculums and industrial training programs. However, the examples used are often not relevant or realistic for process engineers in manufacturing.
In this work, we will share a new industrial batch dataset and make it openly available to other practitioners. We will show how batch processes can be challenging to analyze when having sources of information containing quality, events, and sensor data (tags). We will also introduce machine-learning techniques for troubleshooting and detecting anomalous batches at a manufacturing scale.
| Classification | Both methodology and application |
|---|---|
| Keywords | batch data, industry, open-source |
Primary author
Mr
Benjamin Katz
(Solvay SA)
Co-authors
Philippe Neyraval
(Solvay SA)
Dr
Mattia Vallerio
(Solvay SA)
Dr
Carlos Perez-Galvan
(Solvay SA)
Francisco Navarro
(Imperial College)