What problems does it solve?
Maintenance teams often lack real-time insights into the condition of machines. Repairs are usually performed only after a failure, leading to costly production downtimes. The duration of these downtimes depends on the availability of spare parts, which can cause significant delays.
In the renewable energy sector, a similar issue affects energy installations – wind turbines, solar panels, and energy storage systems. Without continuous monitoring, unexpected failures can lead to energy production losses and high servicing costs.
The best time to react to a failure is before it happens. Predictive maintenance minimizes unplanned downtime and prevents financial losses associated with production stoppages.
What is it and what are the benefits?
Predictive Maintenance is a technology that anticipates failures before they occur, allowing companies to schedule maintenance at the most convenient time. By leveraging real-time data, companies can avoid costly breakdowns, reduce operational risks, and extend equipment lifespan.
In the OZE sector, predictive maintenance ensures high efficiency of energy installations, reduces downtime risks, and lowers operating costs for solar farms, wind farms, and energy storage systems.
How does it work?
Predictive Maintenance technology collects telemetry data from machines using IoT sensors. These sensors transmit key performance parameters – temperature, vibrations, pressure, energy output – which AI-driven algorithms analyze to predict when and which components are likely to require maintenance.
In the renewable energy sector, the system monitors turbines, inverters, and energy storage units, enabling real-time failure detection. When an anomaly is detected, the system sends alerts and recommendations, allowing companies to react proactively and prevent costly downtimes before they occur.
