Nanjing Iron & Steel Co., Ltd. (NISCO) has partnered 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. The announcement, made via Media OutReach Newswire, signals a significant shift in how traditional manufacturers approach digital transformation, moving core operations from experience-based decision-making to data and intelligence collaboration.
The significance of this deployment lies in its measurable impact on core metrics. NISCO reports that 100% of its key equipment is now connected and digitally controlled, new product research and development cycles have been shortened by 50%, and annual costs have been reduced by over CNY100 million (approximately US$15 million). These gains stem from embedding artificial intelligence into every core production stage—ironmaking, steelmaking, rolling, and quality inspection—creating what the company describes as green and high-end AI-powered super steel plants.
Unlike general-purpose monolithic models, YuanYe fuses multiple AI models with the steel industry's 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 and scientific decision-making. Powered by massive amounts of 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, enabling the entire steelmaking process to become not only visible but also capable of precise control and intelligent assessment.
The implications extend beyond cost savings. In ironmaking, AI makes traditionally invisible blast furnaces transparent, allowing 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 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%.
Quality inspection has also been transformed. The integrated smart metallographic inspection system built on YuanYe has achieved full-process automation, raising inspection accuracy to over 95% and shortening per-sample inspection time from 10 minutes to 3–5 minutes, an 80% increase in overall inspection efficiency. In energy and environmental control, the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control integrates 602 process parameters to issue precise 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%.
As of October 2026, NISCO had launched 25 business agents covering scenarios from visual quality inspection to production scheduling. The company 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. Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, emphasized that digital and intelligent transformation is human-centric, aiming to unleash human potential rather than replace people. 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.
Looking ahead, 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. The company aims to provide a replicable and scalable benchmark for the digital and intelligent transformation of the global steel and manufacturing industries, suggesting that the commercial deployment of YuanYe could accelerate AI adoption across the broader industrial sector.
