Issue 7, 2022

Industrial data science – a review of machine learning applications for chemical and process industries

Abstract

In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to start with examples that are irrelevant to process engineers (e.g. classification of images between cats and dogs, house pricing, types of flowers, etc.). However, process engineering principles are also based on pseudo-empirical correlations and heuristics, which are a form of ML. In this work, industrial data science fundamentals will be explained and linked with commonly-known examples in process engineering, followed by a review of industrial applications using state-of-art ML techniques.

Graphical abstract: Industrial data science – a review of machine learning applications for chemical and process industries

Supplementary files

Article information

Article type
Review Article
Submitted
01 dec 2021
Accepted
21 feb 2022
First published
21 apr 2022
This article is Open Access
Creative Commons BY license

React. Chem. Eng., 2022,7, 1471-1509

Industrial data science – a review of machine learning applications for chemical and process industries

M. Mowbray, M. Vallerio, C. Perez-Galvan, D. Zhang, A. Del Rio Chanona and F. J. Navarro-Brull, React. Chem. Eng., 2022, 7, 1471 DOI: 10.1039/D1RE00541C

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements