The additive manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of artificial intelligence (AI) and digital twins (DT). However, current intelligent AM (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction. This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to autonomous AM, featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing. Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Ti6Al4V superalloy is recognized as a good candidate for bone implants owing to its biocompatibility, corrosion resistance, and high strength-to-weight ratio. While dense metal implants are associated with stress shielding issues due to the difference in densities, stiffness, and modulus of elasticity compared to bone tissues, the surface of the implant/scaffold should mimic the properties of the bone of interest to assure a good integration with a strong interface. In this study, we investigated the additive manufacturing of porous Ti6Al4V scaffolds and coating modification for enhanced osteoconduction using osteoblast cells. The results showed the successful fabrication of porous Ti6Al4V scaffolds with adequate strength. Additionally, the surface treatment with NaOH and Dopamine Hydrochloride (DOPA) promoted the formation of Dopamine Hydrochloride (DOPA) coating with an optimized coating process, providing an environment that supports higher cell viability and growth compared to the uncoated Ti6Al4V scaffolds, as demonstrated by the higher proliferation ratios observed from day 1 to day 29. These findings bring valuable insights into the surface modification of 3D-printed scaffolds for improved osteoconduction through the coating process in solutions.