AI in Process Industries – Current Status and Future Prospects

Author:

Bortz Michael1,Dadhe Kai2,Engell Sebastian3,Gepert Vanessa4,Kockmann Norbert5ORCID,Müller-Pfefferkorn Ralph6,Schindler Thorsten7,Urbas Leon8

Affiliation:

1. Fraunhofer Institute for Industrial Mathematics (ITWM) Fraunhofer Platz 1 67663 Kaiserslautern Germany

2. Evonik Operations GmbH Paul-Baumann-Straße 1 45772 Marl Germany

3. TU Dortmund University Department of Biochemical and Chemical Engineering, Laboratory of System Dynamics and Process Control Emil-Figge-Straße 70 44227 Dortmund Germany

4. Air Liquide Forschung und Entwicklung GmbH Gwinnerstraße 27–33 60388 Frankfurt Germany

5. TU Dortmund University Department of Biochemical and Chemical Engineering, Laboratory of Equipment Design Emil-Figge-Straße 68 44227 Dortmund Germany

6. TU Dresden, Center for Information Services and High-Performance Computing 01062 Dresden Germany

7. ABB AG Corporate Research Center Germany Wallstadter Straße 59 68526 Ladenburg Germany

8. TU Dresden, School of Engineering, Chair of Process Control Systems & Process Systems Engineering Group Helmholtzstraße 18 01069 Dresden Germany

Abstract

AbstractThe chemical industry is one of the key industrial sectors in Germany and at the same time one of the largest consumers of energy and raw materials. A successful energy transition and the development of a circular economy can only succeed if they are actively supported and shaped by the chemical industry – through the redesign of existing production processes and the exploration and implementation of new process routes. The challenge is to realize this transformation within a very short time and for many production processes, whereby a much larger number of process routes must be explored. Digital technologies are key to master this transformation towards more sustainability, climate, and environmental protection. The KEEN project aims to explore and leverage artificial intelligence (AI) opportunities in process industry. The newly developed AI methods are tested wherever possible in real working environments and production plants to prove the economic benefit, applicability, and reliability of the methods and technologies.

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Reference59 articles.

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3. www.digitale‐technologien.de/DT/Navigation/DE/Themen/Prozessindustrie/Prozessindustrie.html(last access February 28 2023)

4. cordis.europa.eu/search?q=contenttype%3D%27project%27%20AND%20(%27artificial%27%20AND%20%27intelligence%27%20AND%20%27industry%27)&p=1&num=10&srt=Relevance:decreasing(last access February 28 2023)

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