Realistic interplays between data science and chemical engineering in the first quarter of the 21st century: Facts and a vision

Abstract

Data science, digit(al)ization, Industry 4.0, smart manufacturing: all these terms are receiving heavy interest from industry and funding institutions. While some definitions remain hazy, the financial success of the digital giants has led to a bandwagon all too many companies are happy to jump on. Successes are also reported in the chemical and engineering sciences, driven by specific enablers as well as technical specificities of the application areas. High expectations for data science applications in chemical engineering have resulted, together with a loss of visibility of the limits of a purely data-centric approach. At the same time, chemical engineers may not be fully prepared to embrace the digital revolution in general, and data science in particular. This Short communication, aimed at all stakeholders of the digital transformation of the chemical industry, sets out an aspirational vision for the data science–chemical engineering interplay, together with needs, opportunities, and suggested approaches to address them. Several frameworks are also given to inform technical strategies: activity classes; workflows; and a decision tree to consciously assess what approaches to privilege.