IOT News

Traditional maintenance work order management systems often rely on manual reporting and paper-based records—suffering from delayed information transfer, low processing efficiency, and easily lost data. With the advancement of industrial IoT technology, enterprises urgently need a maintenance management system capable of automatically monitoring equipment status, generating work orders in real time, and intelligently scheduling resources.

To address this, WideIOT offers a maintenance work order management system based on industrial IoT gateways. By deploying industrial IoT gateways on the factory floor and connecting them to PLCs, instruments, industrial robots, CNC machines, and other equipment, the system collects real-time equipment data and enables intelligent alerting—establishing a digitalized maintenance work order management workflow. This ensures real-time monitoring, management, and operation throughout the entire maintenance process—from pre-incident to post-incident—while applying data analytics for continuous optimization and improvement.

Functions

Real-Time Equipment Status Monitoring – Through industrial IoT gateways, the system collects real-time operating status data from equipment across the production line—including key indicators such as temperature, pressure, and vibration.

Abnormal Early Warning and Work Order Generation – Based on intelligent alarm rules, the system automatically identifies abnormal equipment conditions and generates maintenance work orders either automatically or manually—promptly notifying maintenance personnel.

Intelligent Work Order Dispatch – Management personnel intelligently schedule maintenance staff based on work order type, urgency level, and the skill match of technical personnel—ensuring work orders are handled promptly and effectively.

Progress Tracking and Feedback – The system tracks work order processing progress in real time, providing a visualized interface for management personnel to review. It also supports online feedback from maintenance staff on handling results, as well as review and uation.

Data Analytics and Optimization – By collecting maintenance data and performing statistical analysis, the system provides data support for optimizing maintenance strategies—helping improve maintenance efficiency and service quality while reducing operating costs.