Manufacturing industry
Monitoring of CNC spindles, gearboxes, motors and conveyors. Early detection of tool and mechanical component wear.
AnomalySense analyzes the operating history of your machines and adapts to their actual behavior. No manual configuration — the system extracts patterns from historical data on its own.
AI models as an analytics module connected to your PLC, SCADA or MES. AnomalySense enriches the existing system with a predictive layer without replacing the infrastructure.
We design a complete maintenance system with AnomalySense models at the core — from sensors, through integration, to dashboards and alerts. One partner, full responsibility.
The result is a system that signals a problem on its own before it leads to a failure and downtime — without the need for constant operator monitoring.
Data from sensors (e.g. vibration, temperature, pressure, humidity) collected in real time from any number of measurement points.
The model automatically learns the multidimensional normal operating profile of the machine — based on your data, with no configuration required.
Each new measurement is compared against the model. The machine receives an OK or ANOMALY status along with a deviation margin.
Anomaly detection triggers automatic SMS and email notifications to the relevant people — immediately, without monitoring screens.
AI algorithms autonomously identify anomalies in sensor data — without the need to manually define alarm thresholds.
Continuous supervision of machine condition with real-time data refresh — accessible from any device via browser.
Connect any number of sensors of different types. The system grows with the plant without the need to replace infrastructure.
Integration with existing infrastructure without production downtime. Compatible with devices from multiple manufacturers.
Production dashboards and HMI panels presenting machine status, trends and anomaly history in a clear form tailored to the needs of operators and management.
Automatic alerts to the relevant people the moment an anomaly is detected or a threshold is exceeded — immediately, without monitoring screens.
Simple integration with industrial networks and devices from multiple manufacturers via the open IO-Link standard. Wired and wireless.
Early anomaly detection allows maintenance to be planned instead of reacting to failures — a direct impact on the OEE indicator.
AI models work continuously without operator involvement — every anomaly detected automatically and reported immediately.
AI model training on your machine's data without a data engineer — the system learns what is normal on its own.
Monitoring of CNC spindles, gearboxes, motors and conveyors. Early detection of tool and mechanical component wear.
Monitoring of industrial robots, presses, welding machines and hydraulic systems on production lines for the automotive industry.
Continuous monitoring of pumps, blowers and aggregates at water treatment plants and sewage pumping stations operating 24/7.
Monitoring of turbines, generators and rotating equipment at power plants and energy facilities with high reliability requirements.
Monitoring of dosing pumps, mixers and reactors in chemical processes requiring continuous operation and high reliability.
Monitoring of packaging lines, refrigeration equipment and pumps in environments with high sanitary requirements and production continuity.
Monitoring of test stands and measurement equipment in research and development projects requiring precise data recording.
Monitoring of conveyors, sorters and internal transport systems in distribution centers and automated warehouses.
Every implementation starts with a needs analysis — selecting the model configuration, assessing the infrastructure and pricing the project.