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An artificial intelligence course for chemical engineers.

Authors :
Wu, Min
Di Caprio, Ulderico
Vermeire, Florence
Hellinckx, Peter
Braeken, Leen
Waldherr, Steffen
Leblebici, M. Enis
Source :
Education for Chemical Engineers; Oct2023, Vol. 45, p141-150, 10p
Publication Year :
2023

Abstract

Artificial intelligence and machine learning are revolutionising fields of science and engineering. In recent years, process engineering has widely benefited from this novel modelling and optimisation approach. The open literature can offer several examples of their applications to chemical engineering problems. Increasing investments are devoted to these techniques from different industrial areas, but insufficient information on a structured course covering these topics in a chemical engineering curriculum could be found. The course in this paper intends to reduce this gap. We introduce one of the first courses on artificial intelligence applications in a chemical engineering curriculum. The course targets Master's students with a chemical engineering background and insufficient knowledge of statistical approaches. It covers the main aspects by utilising frontal lectures and hands-on exercises with active learning methods. This paper shows the methodology we adapted to introduce students to machine learning techniques and how they responded to each class. The student performances for each test are shown, as well as the survey results based on student feedback and suggestions. This work contains essential guidelines for educators who will provide an artificial intelligence course in a chemical engineering curriculum. • An AI course for chemical engineers is given as one of the first attempts in Europe. • The course is structured into frontal and hands-on lessons. • Modelling and optimisation techniques via AI were shown to the students. • Applications of developed models were explained to the students. • Students can apply basic AI in chemical engineering tasks after this course. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17497728
Volume :
45
Database :
Supplemental Index
Journal :
Education for Chemical Engineers
Publication Type :
Academic Journal
Accession number :
172975080
Full Text :
https://doi.org/10.1016/j.ece.2023.09.004