On the Use of Machine Learning for Additive Manufacturing Technology in Industry 4.0

Abstract

Additive manufacturing (AM) is a crucial component of a smart factory that promises to change traditional supply chains. However, the parts built using state-of-the-art 3D printers have noticeable unpredictable mechanical properties. In this paper, a machine learning (ML) model is proposed as a promising approach to improve the underlying failure phenomena in the AM process. The paper also describe how a ML model can be distributed to form an interactive learning network of smart AM components to fulfil the Industry 4.0 requirements including self-organization, distributed control, communication, and real-time decision-making capability.