Additive manufacturing currently faces challenges such as conflicts between design complexity and manufacturability，difficulties in coordinating materials，processes，and performance，significant quality fluctuations，and high costs. Artificial intelligence （AI） technology offers new solutions to overcome these limitations. This paper reviews the potential application areas of artificial intelligence in the field of additive manufacturing，namely material development，structural design，process optimization，and intelligent equipment. In materials science，AI significantly shortens R&D cycles by accelerating composition design and geometric configuration innovation. For structural design，AI-driven generative design and reverse engineering achieve extreme structural performance and innovation. Regarding process optimisation，AI is employed for process parameter optimisation，performance prediction，design for manufacturability，and error correction，effectively enhancing forming quality and dimensional accuracy. Concerning intelligent equipment，AI-enabled real-time monitoring and adaptive control are propelling additive manufacturing apparatus towards embodied intelligence with perception，cognition，and decision-making capabilities. Building upon existing achievements，this paper further analyses current challenges facing AI，while outlining future directions for achieving fully integrated closed-loop systems and developing autonomous，cognitively embodied intelligent equipment. This aims to provide theoretical guidance for the intelligent upgrading of additive manufacturing.
Yu et al. (Sun,) studied this question.