南京钢铁股份有限公司（南钢）已与华为及生态伙伴合作，在多个场景中规模化商用部署了全球首个由群智驱动的钢铁大模型——元冶钢铁大模型（元冶），这帮助南钢实现了核心业务从依赖经验向依托数据与智能协同的转变。
Nanjing Iron & Steel Co., Ltd. (NISCO) has worked with Huawei and ecosystem partners to commercially deploy the world's first steel model powered by swarm intelligence - the YuanYe Steel Large Model (YuanYe) - across multiple scenarios at scale. This helps NISCO transition its core operations from relying on experience to being powered by data and intelligence collaboration.
作为一家正在应对转型和降本增效挑战的传统制造商，南钢通过采用包括升腾、鲲鹏、华为云Stack和盘古大模型在内的行业领先产品，构建了坚实的数字化和智能化基础。
As a traditional manufacturer navigating the challenges of transformation and cost efficiency, NISCO has built a robust digital and intelligent foundation by adopting industry-leading products including Ascend, Kunpeng, Huawei Cloud Stack, and Pangu models.
通过将人工智能嵌入炼铁、炼钢、轧钢和质检等每一个生产核心阶段，南钢正在打造绿色、高端的人工智能超级钢厂。
By embedding AI into every core stage of production - ironmaking, steelmaking, rolling, and quality inspection - NISCO is forging green and high-end AI-powered super steel plants.
与通用单体模型不同，元冶创新性地将多种人工智能模型与钢铁行业的冶金机理模型相融合，构建了双轮驱动的多模型集群架构。
Unlike general-purpose monolithic models, YuanYe innovatively fuses multiple AI models with the steel industry's metallurgical mechanism models to create a dual-drive, multi-model cluster architecture.
该架构拥有用于概率计算的“右脑”和用于精确科学决策的“左脑”。
This architecture features a "right brain" for probabilistic computing and a "left brain" for precise and scientific decision-making.
依托从26个业务领域的数百万个运营技术（OT）数据点汇聚而成的海量感知数据，南钢在智能运营中心实现了实时数字孪生映射，为元冶奠定了坚实的数据和场景基础。
Powered by massive amounts of sensing data aggregated from millions of operational technology (OT) data points across 26 business domains, NISCO has achieved real-time digital twin mapping within its intelligent operations center, laying solid data and scenario foundations for YuanYe.
这使得整个钢铁制造过程不仅完全可见，而且具备了精确控制和智能评估的能力。
This enables the entire steelmaking process to become not only visible, but also capable of precise control and intelligent assessment.
目前，南钢的关键设备已实现100%连接和数字控制，其新产品研发周期缩短了50%，每年减少成本超过1亿元人民币（约合1500万美元）。
Now 100 percent of NISCO's key equipment is connected and digitally controlled and its new product R&D cycles have been shortened by 50 percent, reducing annual costs by over CNY100m (approx. US$15m).
随着该模型的不断迭代，截至2026年10月，南钢已推出25个业务智能体。
As the model continues to iterate, NISCO had launched 25 business agents by October 2026.
这些智能体涵盖了从视觉质量检测、工艺优化到生产调度和运营管理的广泛场景，为钢铁行业的数字化和智能化转型树立了新标杆。四大核心场景的突破：“远业”重新定义了传统运营，实现了安全性、效率和质量的大幅提升。在炼铁环节，人工智能让原本不可见的高炉变得透明。“远业”利用高炉内部传感器数据和冶金机理分析，对炼铁过程进行实时动态模拟。
These agents cover a wide range of scenarios, from visual quality inspection and process optimization to production scheduling and operations management, setting a new benchmark for digital and intelligent steel transformation. Breakthroughs in four core scenarios: YuanYe redefines traditional operations for significant safety, efficiency, and quality gains In the ironmaking stage, AI makes traditionally invisible blast furnaces transparent. YuanYe leverages blast furnaces' internal sensor data and metallurgical mechanism analysis to perform real-time dynamic simulations of the ironmaking process.
在炉温预测和健康诊断模型的辅助下，炉长能够提前两小时预测温度并识别问题，准确率超过90%。这使高炉操作从反应式的事后补救转向前瞻性的事前控制，优质铁水产出率提高了10%以上，同时显著降低了单位能耗。在轧钢环节，人工智能驱动精准预测并固化专家经验，以增强钢材轧制的运行稳定性，并在产品质量上保持领先。
Assisted by furnace temperature prediction and health diagnosis models, furnace operators can predict temperatures and identify issues two hours in advance, with over 90 percent accuracy. This shifts furnace operations from reactive post-event remediation to proactive pre-control, increasing prime-grade molten iron yield by over 10 percent while significantly cutting unit energy consumption. In the rolling stage, AI drives precise predictions and codifies expert experience to enhance the operational stability of steel rolling and secure leadership in product quality.
为应对轧钢过程中高度动态且复杂的工况，“远业”的轧制力预测模型实现了毫秒级响应，将厚度公差缩小至正负0.2毫米，并将钢材厚度偏差降至1.9%，达到了世界领先标准。轧制力命中率从88%跃升至98%，支持了每年超过250万吨钢板的稳定产量，并将整体成材率提高了0.5%。尺寸精度和物理化学稳定性的提升，使南钢的产品能够满足从大型体育场馆、输油管道到万吨级邮轮和液化天然气储罐等各种应用中严苛的钢铁规格要求。
To tackle the highly dynamic and complex operating conditions during the rolling process, YuanYe's rolling-force prediction model achieves millisecond-level response, narrowing the thickness tolerance to ±0.2 mm and reducing the steel thickness deviation to 1.9 percent to reach a world-leading standard. The rolling-force hit rate has jumped from 88 percent to 98 percent, supporting a steady annual output of over 2.5 million tons of steel plates and increasing the overall yield rate by 0.5 percent. Enhanced dimensional precision and physical-chemical stability allow NISCO's products to meet demanding steel specifications across diverse applications, ranging from mega stadiums and oil pipelines to 10,000-ton cruise ships and LNG storage tanks.
在质量检验中，机器人与人工智能模型的协同发挥着敏锐的“鹰眼”作用，使金相检验效率翻倍。在成品钢金相检验期间，基于“元冶”构建的集成式智能金相检验系统实现了全流程自动化，涵盖样品磨削与抛光、图像采集以及智能评级。检验准确率已上升至95%以上，而每个样品的检验时间从10分钟缩短至3至5分钟。整体检验效率提升了80%，这让操作人员得以腾出精力专注于异常分析与高层决策。
In quality inspection, the synergy between robots and AI models serves as a discerning "eagle eye", doubling metallographic inspection efficiency. During metallographic inspection for finished steel, the integrated smart metallographic inspection system built on YuanYe has achieved full-process automation, covering sample grinding and polishing, image acquisition, and smart grading. Inspection accuracy has risen to over 95 percent, while per-sample inspection time has been shortened from 10 minutes down to 3–5 minutes. This 80 percent increase in overall inspection efficiency frees human operators to focus on anomaly analysis and high-level decision-making.
在能源与环保控制阶段，南钢利用“元冶”架构开发了煤气及烟气脱硫S-Link智能体。该智能体整合了602个工艺参数以及多模态图像和知识能力，实现了贯穿源头预测、过程优化和末端达标的智能闭环。通过将机理反演与时间序列预测相结合，它提前1小时发出精准的硫风险预警，硫预测准确率达到95%以上。随后，运行优化算法在几秒钟内计算出最佳煤气掺混方案。
In the energy and environmental control stage, NISCO leverages the YuanYe architecture to develop the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control. Integrating 602 process parameters alongside multi-modal image and knowledge capabilities, the agent achieves a smart closed loop across source prediction, process optimization, and end-of-pipe compliance. By combining mechanism inversion with time-series forecasting, it issues precise sulfur-risk warnings one hour in advance, achieving a sulfur prediction accuracy of over 95 percent. Operational optimization algorithms then calculate the optimal gas blending scheme within seconds.
最后，博弈论模型动态分配排放配额，使天然气混烧消耗量大幅减少近50%。这使因超标排放导致的停机时间减少了25%以上，并带来了超过60万元人民币（约合9万美元）的年经济效益——实现了环保合规与大幅降本的双赢。从劳动力自动化到赋能于人：定义包容性人工智能的新范式。南钢数字智能一体化发展部总经理兼人工智能研究院院长李金艳表示：“数智化转型本质上是以人为本的。”
Finally, game-theoretic models dynamically allocate emission quotas, slashing natural gas co-firing consumption by nearly 50 percent. This has reduced downtime caused by emission exceedance by over 25 percent, and delivered more than CNY600,000 (approx. US$90,000) in annual economic benefits - securing both environmental compliance and drastic cost reduction. From automating labor to empowering people: Defining a new paradigm of inclusive AI Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, said: "Digital and intelligent transformation is inherently human-centric.
其目的不是取代人类，而是释放人类的潜能。我们的目标是将员工从无边无际的数据海洋中解脱出来，赋能他们将创造力投入到更有价值的工作中去。”截至目前，南钢已在其厂区部署了300多个AI模型，以及由一线员工独立构建的1,000多个低代码智能体和轻量化应用。正如华为钢铁与有色金属军团高级工业解决方案专家程永福所指出：“工业AI的真正价值，只有在它从单点应用扩展到与生产、运营和管理的全面融合时才能实现，这能够释放持久、可扩展的赋能。”
Its purpose is not to replace people, but to unleash human potential. Our goal is to lift employees out of the endless sea of data, empowering them to direct their creative energy toward work of higher value." To date, NISCO has deployed over 300 AI models across its plants, alongside more than 1,000 low-code agents and lightweight applications built independently by frontline employees. As Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, noted: "The real value of industrial AI can only be realized when it expands from single-point applications to comprehensive integration with production, operations, and management, which can unlock sustained, scalable empowerment."
展望未来，随着模型部署的扩大和计算需求的持续增长，南钢将与华为及其他合作伙伴携手，探索建设智能钢厂专用数据中心。以AI原生三级架构（AI原生操作系统、AI原生工厂和AI原生企业）为核心并由元冶模型提供支持，南钢正在加速高质量钢铁发展，旨在为全球钢铁及制造行业的数字化和智能化转型提供一个可复制、可扩展的标杆。由华为提供
Looking ahead, as model deployment expands and computing demands continue to grow, NISCO will team up with Huawei and other partners to explore the construction of dedicated data centers for smart steel plants. Centered on the AI-native three-tier architecture (AI-native OS, AI-native factory, and AI-native enterprise) and powered by the YuanYe model, NISCO is accelerating high-quality steel development, aiming to provide a replicable and scalable benchmark for the digital and intelligent transformation of the global steel and manufacturing industries. Supplied by Huawei