Enhancing efficiency in smart manufacturing processes through agentic artificial intelligence-driven autonomous systems

The Fourth Industrial Revolution represents a major shift from the traditional concept of manufacturing mainly based on physical labor to the implementation of advanced digitized manufacturing processes. This in turn introduces a wide range of advanced production systems and models featuring an ultra-high level of interconnectivity and intelligence, able to respond in real-time to disturbances and cope with internal and external uncertainties. Despite generating huge quantities of data, research shows that the promised capabilities of those Cyber-Physical Systems have not yet reached their full potential. Autonomous Systems focus on improving the physical system level of autonomy without operator oversight, so the inter-agent and intra-agent tensions of these systems become even more challenging, particularly with regards to frictional and/or parasitic losses of the available productivity. These systems may already fuse natural and artificial intelligence, and the incoming and outgoing checks and balances of such technology using Agentic AI will help remove deadlocks from the operational model.