Periodic maintenance of equipment based on fixed time cycle has the problem of high cost and low efficiency cost ratio. Power generation enterprises are actively looking for predictive maintenance schemes based on the health of equipment, to realize the overall reduction of maintenance cost and the effective improvement of equipment utilization rate and maintenance rate.
Lenovo provides the monitoring, early warning and diagnosis, forecast and other four integrated equipment solutions for predictive maintenance to power plant customers, and use the IoT technology to collect comprehensive core components equipment data and business process data, based on mechanism model and artificial intelligence to deeply mines factory equipment status data, real-time comprehensive evaluation equipment health status, and provide equipment health warning and fault diagnosis ability, and predict the equipment life cycle are available, and combining the resources of the maintenance and data analysis ability, to help the power plant customer quickly find potential problems affecting the safe operation of the unit, to predict the failure time of components, evaluate the maintenance cycle, resources and cost, and make effective maintenance plan.
Reduce the potential accidents of equipment and system
Reduce unplanned downtime of critical equipment and systems
Improve the reliability and availability of equipment and systems
Reduce equipment maintenance and operation cost