The KEEN Platform at ECCE 13 & ECAB 6
The KEEN Platform was present with two own sessions at the 13th European Congress of Chemical Engineering & 6th European Congress of Applied Biotechnology (ECCE 13 & ECAB 6). The congress is a highlight event for scientists from industry, academia, and research institutions to discuss the latest research results and industrial applications in all areas of chemistry, chemical engineering, and biotechnology.
Besides the two session with the title "AI in process modelling, design and operation I and II“, KEEN was also present in the session "Separation technologies/ downstream processing - Digitalization" with the following contribution:
L. Neuendorf, J. Oeing, N. Kockmann (2021) Artificial Intelligence in laboratories: Machine and Deep Learning based monitoring of flooding behavior in distillation and extraction columns.
The two sessions, which were organized by KEEN together with the ProcessNet Subject Division Process and Plant Engineering, consisted of seven talks:
- M. Wiedau, G. Tolksdorf (2021) Before you start with AI, get your data in shape!
- J. Oeing, R. Jäkel, N. Kockmann (2021) Uniform data bases as a driver for future process development (data, repositories and application examples)
- S. Merkelbach, B. Bordas, R. Tan, F. D. Bähner, M. Gärtler, S. K. Kurt, A. Bamberg, L. Urbas (2021) Towards Automatic Batch Phase Recognition and Online Monitoring for the Process Industry
- M. Bortz, J. Damay, F. Jirasek, M. von Kurnatowski, P. Ludl, D. Schack, Air Liquide, R. Schmidt, J. Steimel (2021) From substance data to process models – use cases for machine learning in process engineering
- F. Jirasek, N. Hayer, T. Specht, J. Damay, M. Bortz, R. Abbas, B. Schmid, H. Hasse (2021) Hybrid Predictive Fluid Property Models – Integration of Physical Knowledge in Data-driven Matrix Completion Methods
- J. Schöneberger, B. Aker, A. Fricke (2021) Workflow for Building and Analyzing Machine Learning Models based on Rigorous Flowsheet Simulations
- J. Winz, U. Piechottka, S. Assawajaruwan, S. Engell (2021) Model based optimal design of dynamic experiments in gray-box and black-box modeling of fermentation processes
More than 60 participants followed the talks. The chair, Dr. Kai Dadhe from Evonik Operations GmbH, ensured a stimulating final discussion. The speakers agreed that in the future both, data scientists and process engineers, will be equally in demand, as interdisciplinary teams are going to achieve promising results in the field of AI.