Anomaly detection
Get an intelligent system for condition monitoring that will allow you to prevent failures by detecting equipment anomalies. There are over 50 different approaches to anomaly detection, including machine learning methods and multi-criteria analytical methods based on neural networks.
Early detection of anomalies in equipment condition greatly reduces failure repair costs and improves equipment health.
System functionality:
- Automated data entry for repair;
- Anomaly detection with mathematical methods of statistics;
- Classification of anomalous conditions using AI methods;
- Integration with IIoT, process control systems, equipment monitoring.
Tools:
- Archive of condition parameters of each repair object;
- Analysis of condition parameters of the repair objects based on their operating models.
