en.Wedoany.com Report on Mar 30th, In the 2026 "TOP50 Annual Products for Construction Machinery" selection, Sany Loader Division's "Fleet Cluster Intelligent Operation and Maintenance Management System" was awarded the "Annual Recommended Intelligent Solution" prize. This system is an intelligent management platform specifically designed for loader fleets, addressing the equipment operation and management needs in the construction machinery sector.
The "TOP50 Annual Products for Construction Machinery" selection has been held for 19 consecutive years and garners significant attention within China's construction machinery industry. This award first introduced the "Annual Recommended Intelligent Solution" category in 2025, aiming to recognize companies making progress in intelligent and unmanned solutions. Sany Loader's win reflects its technological accumulation in the field of digital operation and management for construction machinery.
Sany Loader's Fleet Cluster Intelligent Operation and Maintenance Management System provides a digital solution covering equipment, personnel, and tasks through a cloud platform and intelligent algorithm architecture. The system comprises three main functional modules: The Equipment Cluster Management Module can obtain real-time information on vehicle location, historical routes, working hours, power consumption, workload, etc., and provides intelligent maintenance reminders; The Fleet Personnel Management Module ensures safety through 360-degree surround view and blind spot monitoring, supporting driver behavior warnings; The Work Task Management Module can automatically generate operational reports and optimize task allocation through data analysis.
The system has already provided customized solutions for multiple industry clients. In a project involving 40 electric loaders at a state-owned steel plant in Yunnan, the system, combined with weighing functionality, enabled automatic calculation of workload and efficiency. In a material management project for an environmental protection company in Guangzhou, the system helped the client improve management efficiency through material identification and classification statistics solutions.
Sany Loader stated that the system aims to address common issues in construction machinery equipment management, such as workload quantification, data statistics, material management, maintenance records, and equipment supervision. In the future, the system will integrate AI, IoT, and big data technologies to further expand its applications in construction machinery construction management.
