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, according to a press release issued via Media OutReach Newswire. The deployment marks a shift in core operations from experience-based decision-making to data- and intelligence-driven collaboration, with the company reporting annual cost reductions exceeding CNY100 million (approximately US$15 million) and improvements in key production metrics.
The YuanYe model differs from general-purpose monolithic models by fusing 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 aggregated 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, 100% of NISCO's key equipment is now connected and digitally controlled, and new product research and development cycles have been shortened by 50%. As of October 2026, NISCO had launched 25 business agents covering scenarios from visual quality inspection and process optimization to production scheduling and operations management.
The model has delivered breakthroughs in four core scenarios: ironmaking, rolling, quality inspection, and energy and environmental control. In ironmaking, YuanYe enables furnace 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 model's rolling-force prediction achieves millisecond-level response, narrowing thickness tolerance to ±0.2 mm and reducing steel thickness deviation to 1.9%. The rolling-force hit rate has jumped from 88% to 98%, supporting a steady 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%, reducing downtime caused by emission exceedance by over 25%, and delivering more than CNY600,000 (approximately US$90,000) in annual economic benefits.
Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, emphasized the human-centric nature of the transformation: "Digital and intelligent transformation is inherently human-centric. Its purpose is not to replace people, but to unleash human potential." 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. Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, noted that the real value of industrial AI is realized when it expands from single-point applications to comprehensive integration with production, operations, and management.
The deployment matters for the broader steel and manufacturing industries because it demonstrates a replicable and scalable benchmark for digital and intelligent transformation. NISCO plans to team up with Huawei and other partners to explore dedicated data centers for smart steel plants, centered on an AI-native three-tier architecture and powered by the YuanYe model, accelerating high-quality steel development. As the model continues to iterate, the collaboration aims to provide a template that other traditional manufacturers can follow in pursuing green, high-end production and cost efficiency.
