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Humaware’s Adaptive Anomaly Detector provides users with trusted actionable information to optimise maintenance schedules and increase asset availability.
The Adaptive Anomaly Detector identifies deviations as anomalies; these include events, discontinuities and trends in the data. Early detection of these types of anomalies is essential for providing enough time to plan and perform maintenance operations during the estimated remaining useful life of the asset.
it is an essential building block for implementing predictive maintenance.
Humaware’s Adaptive Anomaly Detector allows you to create competitive, effective and scalable Condition Monitoring and Predictive Maintenance solutions.
The Adaptive Anomaly Detector is available as a stand-alone solution. APIs allow you to interface with the cloud-based Adaptive Anomaly Detector and view the results in your own interface.
Humaware’s technology has been extensively proven in the rail and aerospace sectors and can be applied to any application which requires the analysis of time series data.
Accurate and early detections are are essential for the implementation of predictive/prescriptive maintenance and the generation of remaining useful life estimates.
SmartVision™ by EKE-Electronics is powered by Humaware’s Adaptive Anomaly Detector to provide a multi-fleet remote diagnostics & predictive condition-based maintenance system for train and track.
The application of Condition Monitoring/Predictive Maintenance to a large population (or fleets) of assets often results in reduced effectiveness of your current solution. Typical issues include:
Many feel that they are left with no choice but to apply individually tailored fixed thresholds for each individual asset in a population. This may not be a problem for you right now, but as your solution scales, the task of setting and managing individual fixed thresholds across hundreds of assets can quickly become unmanageable, distracting valuable resource and extending the time to detect failures.
