Intelligent Equipment Connectivity Management System-Fitow

Intelligent Equipment Connectivity
Management System

Build a new digital collaborative management platform to make equipment
management more transparent, simpler, and smarter

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By leveraging cloud computing, IoT, visual analytics, and industrial AI models, existing enterprise data is refined to help improve equipment operation and maintenance efficiency, balance productivity among devices, and achieve comprehensive equipment lifecycle management.
Information Archiving
Equipment Monitoring
Spare Parts Management
AI-Assisted Decision Making
Multi-Terminal Access
Integration and Compatibility

Equipment ledgers with real-time archiving of inspection, patrol, repair, and maintenance information, enabling full lifecycle information traceability
Enables large-screen real-time monitoring, overall equipment layout visualization, and abnormal risk alarms
Applies algorithm models to assist in processing equipment data and provide intelligent analytical decisions
Supports mobile terminal access with real-time equipment monitoring and alerts to meet real-time operation guidance
Seamlessly integrates with OA, ERP, ERP, MES, and other systems
Spare parts in/outbound query, information statistics, and scientific analysis of usage
Basic Data Modeling
Inspection / Patrol Management
Maintenance Management
Repair Management
Spare Parts Management
Early Warning Management
Knowledge Base
Monitoring Dashboard
Intelligent Operations & Maintenance
The equipment management system mainly includes the
following functions:

Adopts a modular design to flexibly adapt to enterprises of different scales and provide comprehensive and detailed management functions.
工业制造行业

For manufacturing enterprises with a large number of production equipment, the system monitors the operating status and production data of various machines on the production line in real time, promptly detects abnormalities, and avoids losses caused by equipment failures.
Industrial Manufacturing Industry
能源化工行业
For enterprises such as power companies and petrochemical enterprises with critical equipment, the system enables remote monitoring and fault diagnosis to promptly detect and handle equipment failures, ensuring stable energy supply.

Energy and Chemical Industry
In medical institutions and related biotech enterprises, full lifecycle tracking ensures compliant use and improves medical resource utilization efficiency. Regular calibration and maintenance reminders ensure stable performance and safe, reliable equipment.

Biopharmaceutical Industry
公共设施行业
Applied to urban public facilities, commercial property equipment, and retail store equipment. The system enables digital management of public facilities to ensure normal operation.

Public Facilities Industry
Data-Driven Decision Making
Maintenance Management
Intelligent Analysis
Enhance Reliability
Reduce Costs
Improve Efficiency
By monitoring equipment status in real time, predicting maintenance needs, reducing downtime, and optimizing operational processes, maintenance efficiency is significantly improved by 30–45%.
Preventive maintenance reduces the frequency and cost of emergency repairs, extends equipment lifespan by 20–30%, and lowers overall operation and maintenance costs.
Continuous monitoring of equipment performance enables timely identification and resolution of potential issues, ensuring stable operation and enhancing system reliability.
Collects and analyzes equipment data to identify production blind spots, provide data support for enterprises, assist management in making more accurate decisions, and reduce spare parts inventory by 38%.
Product Value

Allows managers to remotely monitor and control equipment, especially in remote areas or hazardous environments, improving management efficiency and safety, and reducing maintenance costs by 24–36%.
Uses artificial intelligence and machine learning to analyze equipment data, scientifically predict equipment failures and performance degradation, provide trend warnings, and significantly reduce equipment failure rates by 18–28%.