Nanjing Iron & Steel Co., Ltd. (NISCO), in collaboration with Huawei and ecosystem partners, has commercially deployed the world's first steel model powered by swarm intelligence—the YuanYe Steel Large Model—across multiple scenarios at scale. The announcement, distributed via Media OutReach Newswire, signals a significant step in the steel industry's digital transformation, moving core operations from reliance on human experience to data- and intelligence-driven collaboration.
The importance of this deployment lies in its tangible results. NISCO reports that 100% of its key equipment is now connected and digitally controlled, new product research and development cycles have been halved, and annual costs have been reduced by over CNY100 million (approximately US$15 million). These gains stem from embedding AI into every core production stage—ironmaking, steelmaking, rolling, and quality inspection—supported by industry-leading products including Ascend, Kunpeng, Huawei Cloud Stack, and Pangu models.
Unlike general-purpose monolithic models, YuanYe fuses multiple AI models with metallurgical mechanism models to create a dual-drive, multi-model cluster architecture. This architecture features a "right brain" for probabilistic computing and a "left brain" for precise, scientific decision-making. Powered by massive sensing data from millions of operational technology data points across 26 business domains, NISCO has achieved real-time digital twin mapping within its intelligent operations center. As a result, the entire steelmaking process is not only visible but also capable of precise control and intelligent assessment.
The model's impact is evident across four core scenarios. In ironmaking, AI makes traditionally opaque blast furnaces transparent, enabling operators to predict temperatures and identify issues two hours in advance with over 90% accuracy, increasing prime-grade molten iron yield by over 10% while cutting unit energy consumption. In rolling, the rolling-force prediction model achieves millisecond-level response, narrowing thickness tolerance to ±0.2 mm and reducing steel thickness deviation to 1.9%, a world-leading standard. The rolling-force hit rate has jumped from 88% to 98%, supporting annual output of over 2.5 million tons of steel plates and increasing the overall yield rate by 0.5%. In quality inspection, an integrated smart metallographic inspection system has doubled efficiency, raising inspection accuracy to over 95% and reducing per-sample inspection time from 10 minutes to 3–5 minutes. In energy and environmental control, the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control issues sulfur-risk warnings one hour in advance with over 95% accuracy, slashing natural gas co-firing consumption by nearly 50% and reducing downtime caused by emission exceedance by over 25%.
Beyond operational metrics, NISCO emphasizes a human-centric approach. Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, stated that digital and intelligent transformation is "not to replace people, but to unleash human potential." To date, NISCO has deployed over 300 AI models 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 is realized when it expands from single-point applications to comprehensive integration with production, operations, and management.
Looking ahead, NISCO plans to explore dedicated data centers for smart steel plants with Huawei and other partners, centered on an AI-native three-tier architecture. This deployment not only sets a benchmark for the global steel and manufacturing industries but also demonstrates how traditional manufacturers can achieve green, high-end, and intelligent operations at scale.
