Our work, "Digital Twin-based AI Large Model Enhancement Platform", focuses on the pain points of industrial automation scenarios and builds a "three-tier, three-domain, double-closed-loop" architecture that integrates digital twin and AI large model technologies. The hardware takes STM32 core board as the center, combines camera, Bluetooth, microphone and other modules, and combines Google Speech-to-Text speech recognition and xunfei spark natural language processing technology to realize intelligent control of hardware such as intelligent vehicle movement and mechanical arm control. Software development parallel processing, edge calculation optimization, ML fault monitoring and other algorithms, relying on multi-source heterogeneous database and data full life cycle management, achiever nanosecond synchronization between physical space and digital space, and second-level closed-loop issuance of decision instructions. The platform can monitor the operation status of the industrial physical network in real time, accurately predict equipment failures, optimize the production process, and visually display equipment operation parameters and production data through the upper computer visual interface, providing intelligent solutions for industrial enterprises to improve production efficiency and reduce operating costs, with both technical innovation and scene practicality.