Every machine is subject to the risk of breakdown resulting in a loss of productivity or even in serious accidents, particularly for key critical equipment.
Predicting the risk of breakdowns and acting swiftly in the event of a risk of malfunction makes it possible to reduce the frequency of failures and organize maintenance operations more efficiently.
IT Link for Work has developed a system for collecting and processing smart data from IoT devices located over wide geographical areas in order to implement a predictive maintenance process.
The solution can manage the acquisition and transfer of measurements from multiple sensors located on sensitive infrastructures. Using a machine learning algorithm, it analyzes historical data and detects inconsistent signals indicating a risk of malfunction, triggering preventive maintenance actions as a result.