5GDeploymentsManufacturing

Chinese Steel Giants Deploy 5G Private Networks for Smart Manufacturing   

Smart manufacturing PrivateLTEand5G

Vertical: Manufacturing

Application: Remote crane control, autonomous vehicle operations, AI-powered quality inspection, intelligent material handling, environmental monitoring, production line automation

Ecosystem:  ZTE, China Unicom, China Telecom, Huawei,

Private Network: 5G

China’s steel industry is embracing advanced wireless connectivity as major manufacturers deploy comprehensive 5G private networks to modernize their operations. Two prominent cases – Wuhan Iron and Steel Corporation and Baoshan Iron & Steel – demonstrate how dedicated cellular networks are enabling new levels of automation and efficiency in heavy manufacturing environments.

Wuhan Iron and Steel Corporation, in partnership with Hubei Unicom and ZTE, has constructed what is described as one of China’s largest 5G enterprise private networks. The deployment spans 63 shared base stations across the factory complex, achieving over 95 percent coverage throughout the facility. According to the requirements of intelligent manufacturing business and the characteristics of the iron and steel industry, Hubei Unicom chose independent private network mode to build the largest 5G private network in China for WISCO.

The network architecture employs what the companies call a “1+N+X” model – one exclusive core network, multiple shared base stations, and integrated industrial control private networks. This configuration allows the steel manufacturer to maintain complete control over its communications infrastructure while supporting diverse industrial applications across different production areas.

The entire 5G network is independently operated by WISCO, and all security policy rights are fully controlled, achieving the highest level of security, control and management. The core network equipment is housed entirely within the factory premises, eliminating the need to backhaul data through external networks. Its outdoor coverage tested reaches 99.02%, with an average downlink throughput of 800.59 Mbps and an average uplink throughput of 150.78 Mbps.

Practical applications showcase the technology’s impact on steel production processes. Large-scale unmanned driving systems now operate across hot rolling, cold rolling, and silicon steel production lines. Remote control systems manage overhead cranes and material handling equipment, allowing operators to work from centralized control rooms away from hazardous environments. Numerous applications tailored to iron and steel scenarios, such as 5G+ autonomous driving, 5G+ intelligent iron water dispatching, 5G+ high-risk operation monitoring, and 5G+ ecological protection have been successfully implemented.

Baoshan Iron & Steel has pursued a similar approach in collaboration with China Telecom and Huawei. Their deployment emphasizes deterministic networking capabilities specifically designed for precision industrial control. By deploying 5G deterministic network, the company recycled 250,000 tons of scrap steel, and reduced carbon dioxide emissions by 1.732 million tons in 2022. The network supports AI-powered scrap steel grading systems and automated surface quality inspection processes.

Technical innovations in both deployments address the unique challenges of steel manufacturing environments. The system guarantees deterministic low latency (10ms), controllable jitter (us level) and accurate synchronization. Dual-link redundancy systems ensure continuous operation even when individual network components experience failures. Frame Replication and Elimination for Reliability protocols provide additional protection for critical control systems.

Safety improvements constitute a significant benefit of the new network capabilities. Remote operation of cranes and other heavy equipment reduces worker exposure to dangerous environments involving molten metal and hazardous materials. AI-assisted monitoring systems can detect potential safety issues more quickly than manual inspection processes.

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