AI for Manufacturing and Healthcare: a chemistry and engineering perspective

TL;DR

This review explores how AI is transforming manufacturing and healthcare by enabling new capabilities like molecule design, predictive maintenance, and medical diagnostics, emphasizing recent applications and challenges.

Contribution

It provides a comprehensive overview of AI applications in manufacturing and healthcare, highlighting recent advances, specific domains, and related topics like explainability and security.

Findings

AI enhances efficiency in chemical and medical processes

AI enables new capabilities like autonomous systems and molecule design

Discussion of challenges in AI deployment in industry and healthcare

Abstract

Artificial Intelligence (AI) approaches are increasingly being applied to more and more domains of Science, Engineering, Chemistry, and Industries to not only improve efficiencies and enhance productivity, but also enable new capabilities. The new opportunities range from automated molecule design and screening, properties prediction, gaining insights of chemical reactions, to computer-aided design, predictive maintenance of systems, robotics, and autonomous vehicles. This review focuses on the new applications of AI in manufacturing and healthcare. For the Manufacturing Industries, we focus on AI and algorithms for (1) Battery, (2) Flow Chemistry, (3) Additive Manufacturing, (4) Sensors, and (5) Machine Vision. For Healthcare applications, we focus on: (1) Medical Vision (2) Diagnosis, (3) Protein Design, and (4) Drug Discovery. In the end, related topics are discussed, including physics integrated machine learning, model explainability, security, and governance during model deployment.