Artificial Intelligence in Process Engineering

TLDR

Artificial Intelligence has surged due to advances in computing, techniques, and software, and while it has begun to benefit process engineering, the field’s methods remain diverse and many opportunities are still untapped. This paper aims to provide a systematic overview of the current state of AI and its applications in process engineering. The authors classify existing AI applications, techniques, and preprocessing/postprocessing steps, highlight reverse‑engineering and hybrid modeling approaches, and propose a holistic strategy for applying AI in process engineering.

Abstract

In recent years, the field of Artificial Intelligence (AI) is experiencing a boom, caused by recent breakthroughs in computing power, AI techniques, and software architectures. Among the many fields being impacted by this paradigm shift, process engineering has experienced the benefits caused by AI. However, the published methods and applications in process engineering are diverse, and there is still much unexploited potential. Herein, the goal of providing a systematic overview of the current state of AI and its applications in process engineering is discussed. Current applications are described and classified according to a broader systematic. Current techniques, types of AI as well as pre‐ and postprocessing will be examined similarly and assigned to the previously discussed applications. Given the importance of mechanistic models in process engineering as opposed to the pure black box nature of most of AI, reverse engineering strategies as well as hybrid modeling will be highlighted. Furthermore, a holistic strategy will be formulated for the application of the current state of AI in process engineering.