Project Meetings

Final conference at DECHEMA on 22.-23.05.2023

Keynote lecture:

Are we still keen on AI? Sibylle Mutschler (Postfinance & KEEN Spiegelgremium)  

KEEN-presentations:

From thermodynamics to processes: AI facing small data and big models - Michael Bortz (Fraunhofer ITWM)  

Explainable Optimization via explainable AI - Dominik Schack, Robin Schmidt, Vanessa Gepert (AirLiquide) & Marco Baldan, Patrick Ludl, Michael Bortz (Fraunhofer ITWM)  

Smart Engineering – KI-Assistenz in Prozesssimulation und R&I-Planung - Norbert Kockmann (TU Dortmund) & Wolfgang Welscher (X-Visual Technologies)  

Selbstoptimierende Anlage mit KI – wie weit sind wir gekommen? - Sebastian Engell (TU Dortmund)

Kognitive Sensoren als Voraussetzung für KI-Algorithmen - Laura Neuendorf (TU Dortmund) & Christiane Schlander (Merck)  

Recipe optimization of batch distillation trajectories based on a data-driven model - Gerardo Brand Rihm, Erik Esche, Jens-Uwe Repke (TU Berlin) & Merlin Schüler, Corina Nentwich, Michael Kawohl (Evonik)  

PID bis KI: optimale Kolonnenregelung in KEEN - was lernen wir daraus? - Stefan Krämer, Yak Ortmanns, Jörn Felix Hecht, Volker Roßmann (Bayer) & Mohamed Elsheikh, Sebastian Engell (TU Dortmund)  

Development and utilization of a dynamic gray-box model for a fermentation process of a sporulating bacterium - Joschka Winz, Sebastian Engell (TU Dortmund) & Supasuda Assawajaruwan, Uwe Piechottka (Evonik)  

Viele Daten, wenig Information – neue Wege zur Nutzung operativer Prozessdaten - Leon Urbas (TU Dresden)

Systematisches Datenmanagement als Grundlage für KI - Ralph Müller-Pfefferkorn, Lincoln Sherpa, Valentin Khaydarov, Leon Urbas (TU Dresden) & Gregor Tolksdorf, Michael Kawohl, Michael Wiedau (Evonik) & Udo Enste (Leikon) & Marco Gaertler (ABB) & Martin Krawczyk-Becker (Krohne) & David Wagner-Stürz (Samson Group)  

Deep Learning for Computer Vision in Process Industry - Valentin Khaydarov, Leon Urbas (TU Dresden)  

Active learning and transfer learning for process analytics - Chen Song, Ruomu Tan, Marco Gärtler, Martin Hollender, Sylvia Maczey (ABB) & Franz Baehner (Bayer) & Bram Bamps (Covestro)  

 

Project meeting on 26.04.2021: Poster session

J. Oeing, N. Kockmann (2021) Standardization of HAZOP-studies for application of Artificial Intelligence

V. Khaydarov (2021) Recognition of Flow Regime and Evaluation of KPI in Aerated Stirred Tanks

L. Sherpa, R. Jäkel, R. Müller-Pfefferkorn (2021) Making Data Shareable - the Keen Data Management Platform

J. Schöneberger, B. Aker, A. Fricke, M. Kawohl, Ch. Hiller, V. Khaydarov (2021) Broaden the Operation Window for a Batch Distillation

Z. Charania, M. Krawczyk-Becker, U. Enste, D. Wagner-Stürz, L. Urbas (2021) Efficient Integration Architecture For Enabling AI-Based Applications In Brownfield Plants

R. Tan, B. Kloepper (2021) An overview of plant data for machine learning: categories, availability, and common problems

A. Fricke, B. Aker, J. C. Schöneberger (2021) Interaction of Process Engineers and Software Tools in Machine Learning (ML)

B. Bordas, M. P. Galvis Cordoba, K. Kurt, A. Bamberg, P. Sander, D. Bleidorn, Ch. Sonntag (2021) AI-driven Optimization, Monitoring and Decision Support for Batch Plants

J. Oeing, W. Welscher, N. Kockmann (2021) Artificial Intelligence supported P&ID-development

V. Khaydarov, J. Schöneberger, S. Blumenschein, M. Schleehahn (2021) Operating window exploration of continuous reaction plant

F. Bähner, M. Gärtler, B. Klöpper, S. Maczey, S. Merkelbach, P. Sander, C. Song, C. Sonntag, R. Tan (2021) Towards Automatic Batch Phase Detection: First Results using Machine Learning

J. Winz, U. J. Ravali Theeda, B. Bordas, K. Kurt, A. Bamberg, S. Engell (2021) Hybrid modeling and control of a batch distillation process of polymer solutions

S. Lammers, A. Lasch (2021) Does AI have to be humanoid?

L. Neuendorf, Ch. Schlander, B. J. Franks (2021) Preselection of separation units and ML-supported operation of an extraction column

J. Oeing, F. Henke, N. Kockmann (2021) AI-supported prediction of separation processes

G. Brand Rihm, E. Esche, J.-U. Repke, C. Nentwich, Ch. Hiller, M. Kawohl (2021) Training of data-driven models for real-time optimization of operation trajectories of distillation processes