Solution for Equipment Fault Alarm and Maintenance System in Steel Factories

The steel industry is a typical process manufacturing sector, involving numerous key production equipment in processes such as ironmaking, steelmaking, hot rolling, cold rolling, and waste gas and water treatment. These processes operate continuously for extended periods under harsh working conditions, where the stable and reliable operation of equipment directly impacts production efficiency and operating costs. Equipment failures can disrupt the production sequence, often resulting in the shutdown of entire production lines, causing significant economic losses, environmental pollution, and even personal injuries.

Industry Pain Points

1. High Fault Rate: Steel production equipment often operates under extreme temperatures and heavy loads, leading to frequent failures.
2. Delayed Maintenance: Traditional reliance on manual experience for judgment often results in maintenance work lagging behind problem occurrences.
3. Data Disconnection: Lack of effective data analysis tools makes predictive maintenance a distant goal.
4. Safety Hazards: Failure to promptly detect and address faults may lead to safety accidents.

Solution

To tackle these challenges, WideIOT offers a secure and reliable solution for an intelligent equipment fault alarm and predictive maintenance system.

 This system connects sensors, PLCs, and other devices through IoT gateways, collecting real-time data and uploading it to local upper computers or cloud platforms. This enables real-time monitoring of equipment status, automatic fault detection and alarming, and precise, predictive, and preventive maintenance work through a maintenance system, effectively enhancing equipment management levels and ensuring production efficiency and product quality.

System Functions

1. Real-time Monitoring: Continuously monitors key parameters from PLCs and sensors, providing uninterrupted monitoring of the entire lifecycle of industrial equipment such as motors, pumps, fans, compressors, and gearboxes.
2. Anomaly Detection: Detects abnormal data and sends timely alerts via WeChat, SMS, or email, enabling maintenance before fault shutdowns and ensuring seamless production.
3. Operation and Maintenance Management: Establishes an online, visual, and traceable maintenance process, enabling creation, management, query, and editing of maintenance work orders to ensure efficient maintenance operations.
4. Preventive Maintenance: Assesses potential future issues based on historical data and current status, prioritizes tasks, and guides timely predictive maintenance work to achieve intelligent maintenance.