Abstract
Additive Manufacturing (AM), also known as 3D printing, has revolutionised traditional production methods by enabling layer-by-layer fabrication of complex geometries with reduced waste and enhanced customisation. This chapter provides a brief introduction to AM key processes such as Vat Photopolymerisation, Material Extrusion, Binder Jetting, Directed Energy Deposition, Powder Bed Fusion, Sheet Lamination, and Material Jetting. Then, it importantly deals with the integration of Artificial Intelligence (AI) and Machine Learning (ML) to address AM challenges like process variability, defect detection, and optimisation. Key machine learning approaches, such as regression models, classification algorithms, neural networks, and reinforcement learning, are presented in relation to AM processes. Case studies from the existing literature emphasise advances in defect prediction, material design, and real-time monitoring, while also noting constraints such as data shortages and model interpretation. Future directions prioritise autonomous systems, sustainable practices, and hybrid AI-physics models. Drawing on current research, this chapter emphasises AI/ML’s role in transforming AM into predictive, efficient manufacturing in Industry 4.0.