An artificial intelligence course for chemical engineers

被引:1
|
作者
Wu, Min [1 ]
Di Caprio, Ulderico [1 ]
Vermeire, Florence [2 ]
Hellinckx, Peter [3 ]
Braeken, Leen [1 ]
Waldherr, Steffen [2 ,4 ]
Leblebici, M. Enis [1 ]
机构
[1] Katholieke Univ Leuven, Ctr Ind Proc Technol, Dept Chem Engn, Agoralaan Bldg B, B-3590 Diepenbeek, Belgium
[2] Chem Reactor Engn & Safety CREaS, Leuven Arenberg, Celestijnenlaan 200f-Box 2424, B-3001 Leuven, Belgium
[3] Univ Antwerp Imec, Fac Appl Engn, IDLab, Sint Pietersvliet 7, B-2000 Antwerp, Belgium
[4] Univ Vienna, Fac Life Sci, Dept Funct & Evolutionary Ecol, Mol Syst Biol MOSYS, A-1030 Vienna, Austria
关键词
Modelling; Optimisation; Chemical engineering; Artificial intelligence; !text type='Python']Python[!/text;
D O I
10.1016/j.ece.2023.09.004
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
引用
收藏
页码:141 / 150
页数:10
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