When an industrial hub renowned for its rail transit and advanced manufacturing actively opens its doors to artificial intelligence, a deep integration of industry transformation is already on the horizon. At a recent AI Innovation Conference, Zhuzhou City in Hunan officially released the first list of enterprise application scenarios for "AI + Manufacturing," releasing intelligent demand from more than 30 companies covering 51 specific pain points, accurately anchoring abstract AI technologies to pressing challenges in real production lines.

This list is not a vague technological vision, but a practical map rooted in the full value chain of Zhuzhou's advantageous industries. From raw material processing, core component manufacturing to complete machine assembly and maintenance services, the entry points for AI have been refined into specific tasks that are executable and verifiable. Among them, intelligent industrial software and embodied intelligence have become two strategic focuses— the former aims to break foreign monopolies and build an independent and controllable digital design and simulation toolchain; the latter focuses on enabling robots to truly "understand" the physical environment and complete complex operations, moving toward autonomous decision-making at the manufacturing site.

Leading enterprises take the initiative to put forward "questions." CRRC Zhuzhou Electric Locomotive Co., Ltd. proposed the scenario of "welding quality inspection and monitoring analysis," directly addressing the quality control bottleneck in high-end equipment manufacturing. Traditional welding quality inspection relies on manual sampling or post-event tracking, which is inefficient and difficult to prevent defects. This scenario plans to introduce a machine learning model to analyze multi-source data such as current, voltage, and thermal imaging in real-time during the welding process, predict potential defects in advance, and reconstruct the entire process quality traceability system, achieving a paradigm shift from "post-event correction" to "pre-event prevention."

To ensure these high-value scenarios go beyond paper, the Zhuzhou High-tech Zone has simultaneously built a supporting ecosystem combining both soft and hard measures. Online, relying on the AI "Huama Community" platform, algorithm developers, solution providers, and manufacturing enterprises are gathered to achieve efficient matching of needs and capabilities; offline, an entity innovation center is established, providing testing verification environments and engineering guidance. In addition, by holding the Intelligent Industrial Software Innovation Competition, local R&D vitality is stimulated, and a regional computing power network is also being built to provide underlying support for model training and deployment.

This scenario opening marks that Zhuzhou is transitioning from a "manufacturing highland" to an "intelligent manufacturing source." No longer satisfied with passively applying mature technologies, it is actively defining the "Zhuzhou standard" for AI implementation, driven by real industrial problems. When the 51 scenarios are gradually overcome, the accumulated methodologies and technical assets may offer a replicable and scalable path for the intelligent upgrade of China's manufacturing industry.