"Empowering a New Era of Mining—Zhongyun Kangchong Technology and Guizhou Yuneng Forge Strategic Partnership to Jointly Build the Smart Mine's New Infrastructure"

Recently, Wuhan Zhongyun Kangchong Technology Co., Ltd. successfully completed the beneficiation plant project with Guizhou Yune Mining Co., Ltd. 280 Ten thousand tons / The signing of the contract for the annual smart mine automation, informationization, and intelligent system integration project marks the official entry of our collaboration into the implementation phase! The winning bid for this project amounts to RMB 30.6 million yuan exactly (￥ 30,600,000 ), serving as another strong testament to the company's technological prowess and industry reputation in the field of industrial intelligence.

New Progress on the Project
The technical solution has been fully implemented.
Based on the contract requirements, our company will deploy our independently developed industrial predictive maintenance system, integrating intelligent sensing, AI Algorithm and big data analytics technologies enable full-lifecycle health management for mineral processing equipment, helping customers reduce the risk of breakdowns and downtime while boosting production efficiency.
• Full-process automated control:   Through PLC (Programmable Logic Controller) and DCS (Distributed Control System) Deeply integrated to achieve unmanned, precise control across process sections such as crushing, grinding, and flotation, significantly boosting production efficiency. 20% That's all.
• Digital Twin Modeling:   Construct a 3D digital twin platform for the beneficiation plant, enabling real-time mapping of equipment operating conditions, combined with simulation-based prediction to optimize production parameters and shorten the process debugging cycle. 30%。
• Cloud-based Collaborative Operations and Maintenance:   Leveraging industrial IoT technology, equipment operation data is uploaded in real time to a private cloud platform, enabling remote expert diagnostics and proactive fault management while reducing on-site maintenance response times. 60%。

Efficient fulfillment, professional assurance
The project team has fully launched the implementation plan, strictly adhering to the tender documents and contract terms, ensuring timely completion of critical milestones such as equipment installation, system debugging, and personnel training, ultimately delivering high-quality results to our client.
• Intelligent Training System:   Adopt AR (Augmented Reality) technology simulates equipment operation scenarios, enabling technicians to undergo immersive on-the-job training and significantly improving their skill proficiency rates. 45%。

Deeply cultivating the industry, empowering transformation
Guizhou Yuneng Mining Beneficiation Plant has an annual processing capacity of 280 Ten thousand tons—this is a benchmark project for the intelligent upgrading of mining operations in the southwestern region. Our company leverages our technological expertise accumulated in the field of industrial predictive maintenance, such as ** Equipment failure prediction accuracy exceeds 98%** Its industry-leading expertise and extensive experience in industry services help customers achieve a transformative leap from traditional manufacturing to intelligent, digital operations.
• Energy Efficiency Optimization Closed Loop:   Through AI The algorithm dynamically analyzes energy consumption data and automatically adjusts equipment load as well as start-stop strategies, projecting annual electricity cost savings of over 150 Ten thousand yuan.

Future Promise
Wuhan Zhongyun Kangchong Technology will take this collaboration as an opportunity to continuously enhance its technological innovation capabilities, providing global industrial enterprises with smarter, more efficient, and highly reliable solutions. We firmly believe that, with the relentless efforts of our dedicated team, this project will become a benchmark initiative in the field of mining automation!

Hand in hand, co-creating value through smart manufacturing!
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(Note: The data and project information in this document are based on signed contracts and publicly available bidding documents, and are authentic and valid.)