<p>With the global emphasis on sustainable development and environmental protection, adopting advanced technologies to optimize the use of thermal energy and logistics management in manufacturing systems has become an important task for the industrial sector. The study reviewed the current research status of flexible manufacturing systems and their applications in thermal energy optimization and logistics management. Subsequently, a design scheme for a flexible manufacturing system based on artificial intelligence was proposed, with a focus on analyzing the key technologies of system structure, production cycle scheduling, real-time data correction, and machine tool thermal optimization. By optimizing production pace and real-time data monitoring, the system's responsiveness and efficiency have been significantly improved. This study explores logistics innovation in manufacturing systems for green supply chain management, including logistics scheduling adjustment, production logistics graph network modeling, and model evaluation. After analyzing the environmental impact of transportation and warehousing, sustainable logistics solutions were proposed to reduce resource waste and promote ecological environment protection. Through empirical analysis, the results show that the application of artificial intelligence based flexible manufacturing systems in thermal energy optimization and logistics innovation effectively improves resource utilization and production efficiency, creates higher value in logistics management, and provides new paths and solutions for achieving sustainable development goals.</p>