The future of manufacturing is being shaped by the convergence of embodied artificial intelligence, digital twins, foundation models, and advanced industrial intelligence. As manufacturing systems evolve beyond traditional automation, intelligent entities are expected to perceive dynamic environments, reason about complex situations, make autonomous decisions, and execute adaptive actions across the manufacturing lifecycle. Such capabilities require the seamless integration of physical systems, computational intelligence, industrial knowledge, and human expertise. Recent advances in embodied AI, digital twins, intelligent optimization, industrial large models, predictive analytics, and collaborative intelligence are accelerating the transition toward autonomous and adaptive manufacturing systems. By strengthening the connections between the physical and digital worlds, these technologies enable manufacturing systems to continuously learn, evolve, and optimize their performance in increasingly complex environments. The contributions collected in this Special Issue reflect this emerging paradigm and highlight the ongoing transformation of manufacturing toward more intelligent, resilient, sustainable, and human-centered industrial eco-systems.
