Machine learning and process systems engineering for sustainable chemical processes–A short review

Abstract

This work provides an overview of recent applications of machine learning (ML) to process systems engineering problems related to sustainability. The review is organized by the type of ML problem being solved: regression, classification, and clustering. For each type of problem, we provide references that cover pertinent applications. The review targets a reader interested in learning where to educate themselves on the main algorithms for each type of ML problem, and where to get relevant examples. The article ends with a brief discussion of the current limitations of ML tools and good practice suggestions.