Machine Learning in Chemical Engineering: A Perspective

Chemie Ingenieur Technik, vol. 93, pp. 2029–2039

Abstract

Abstract The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio‐)catalysts, and functional materials. Recent breakthroughs in machine learning (ML) provide unique opportunities, but only joint interdisciplinary research between the ML and chemical engineering (CE) communities will unfold the full potential. We identify six challenges that will open new methods for CE and formulate new types of problems for ML: (1) optimal decision making, (2) introducing and enforcing physics in ML, (3) information and knowledge representation, (4) heterogeneity of data, (5) safety and trust in ML applications, and (6) creativity. Under the umbrella of these challenges, we discuss perspectives for future interdisciplinary research that will enable the transformation of CE.

Authors 7

1. Artur M. Schweidtmann corresponding Aachen

   RWTH Aachen University · Delft University of Technology

   Affiliation as printed

   Delft University of Technology Department of Chemical Engineering Van der Maasweg 9 2629 HZ Delft The Netherlands

   RWTH Aachen University Aachener Verfahrenstechnik Forckenbeckstr. 51 52074 Aachen Germany

   Delft University of Technology, Department of Chemical Engineering, Van der Maasweg 9, 2629 HZ Delft, The Netherlands

   RWTH Aachen University, Aachener Verfahrenstechnik, Forckenbeckstr. 51, 52074 Aachen, Germany

2. Erik Esche

   Technische Universität Berlin

   Affiliation as printed

   Technische Universität Berlin Fachgebiet Dynamik und Betrieb technischer Anlagen Straße des 17. Juni 135 10623 Berlin Germany

3. Asja Fischer

   Ruhr University Bochum

   Affiliation as printed

   Ruhr-Universität Bochum Department of Mathematics Universitätsstraße 150 44801 Bochum Germany

4. Marius Kloft

   University of Kaiserslautern

   Affiliation as printed

   Technische Universität Kaiserslautern Department of Computer Science Erwin-Schrödinger-Straße 52 67663 Kaiserslautern Germany

5. Jens‐Uwe Repke

   Technische Universität Berlin

   Affiliation as printed

   Technische Universität Berlin Fachgebiet Dynamik und Betrieb technischer Anlagen Straße des 17. Juni 135 10623 Berlin Germany

6. Sebastian Säger

   Otto-von-Guericke-Universität Magdeburg

   Affiliation as printed

   Otto-von-Guericke-Universität Magdeburg Department of Mathematics Universitätsplatz 2 39106 Magdeburg Germany

7. Alexander Mitsos Aachen

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Forschungszentrum Jülich Institute for Energy and Climate Research IEK-10 Energy Systems Engineering Wilhelm-Johnen-Straße 52428 Jülich Germany

   JARA Center for Simulation and Data Science (CSD) Aachen Germany

   RWTH Aachen University Aachener Verfahrenstechnik Forckenbeckstr. 51 52074 Aachen Germany

   JARA Center for Simulation and Data Science (CSD), Aachen, Germany

   RWTH Aachen University, Aachener Verfahrenstechnik, Forckenbeckstr. 51, 52074 Aachen, Germany