Application of Machine Learning Techniques in Additive Manufacturing: A Review

Abstract

This chapter provides an analysis of the state-of-the-art in ML applications for optimizing the additive manufacturing process. This chapter primarily presents a review of the literature on the use of machine learning (ML) in optimizing the additive manufacturing process at various stages. The chapter identifies ML-researched areas in which ML can be used to optimize processes such as process design, process plan and control, process monitoring, quality enhancement of additively manufactured products, and so on. In addition, general literature on the intersection of additive manufacturing and machine learning will be presented. The benefits and drawbacks of ML for additive manufacturing will be discussed, as well as existing obstacles that are currently limiting applications.

Impact of Machine/Deep Learning on Additive Manufacturing: Publication Trends, Bibliometric Analysis, and Literature Review (2013-2022).

“…The ML algorithms could also identify flaws and real-time modulation of printing parameters. More recently, [46] highlighted that ML is a valuable approach for optimizing various stages of AM, such as process design, planning, monitoring and control of processes, and an analysis of product quality. In addition, ML can be used to enhance process efficiency, reduce costs, and product quality.…”