Challenge — Anomaly Detection for Industrial Sensors & Lack of Predictive Maintenance
Industrial machines often rely on analysis equipment whose sensors must be maintained manually. This creates significant operational effort and makes predictive maintenance difficult, since early signs of sensor degradation are not systematically detected from the data.
Solution — Time-Series AI for Sensor Anomaly Detection (LSTM & Transformer)
We use time-series AI models such as LSTMs and encoder–decoder Transformer networks to analyze sensor time series and flag implausible values. This makes it possible to detect early indicators that a sensor is degrading and to trigger proactive maintenance actions.
Impact — Reduced Downtime & Earlier Maintenance Actions
- Up to 20% reduction in maintenance intervals and downtime
- Abnormal behavior of analysis equipment is identified in advance, enabling operators to be notified to replace sensors early
Topic
Digital Transformation