Decentralized Manufacturing System

Decentralized manufacturing systems aim to optimize production processes by distributing control and decision-making among independent units, improving flexibility and resilience. Current research focuses on developing efficient algorithms, such as those based on potential games and Stackelberg strategies, to coordinate these units and achieve optimal performance across multiple objectives, including production efficiency and resource consumption. These advancements leverage machine learning techniques like transfer learning and knowledge distillation to enhance the learning and adaptation capabilities of individual units within the system. The resulting improvements in efficiency, adaptability, and resource utilization have significant implications for various industries, particularly those requiring customized products or rapid response to changing demands.