When you think Industry 4.0, there are significant opportunities to leverage sensing, processing and networking technologies to optimize service timing and costs across the lifecycles of plant machinery like compressors, pumps, spindles and motors, as well as to identify leaks and discharges on pressurized tubes and vessels.
In Condition Monitoring, Vibration Analysis can provide early identification of potential issues such as misalignment or bearing failure, and to track the gradual degradation of critical components over time, while Motor Current Signal Analysis helps indicate anomalies associated with imbalances.
Predictive Maintenance represents the highest layer in modern industrial service and maintenance strategies by applying statistical analyses and Machine Learning models to Condition Monitoring data in order to derive estimates regarding remaining machine and component lifetime.
Contents
- Condition based monitoring typical application
- Factory Automation
- Power, Energy & Utilities
- Home Appliances and Building Automation
- Structural Health Monitoring
- ST's portfolio for condition monitoring and predictive maintenance in industry 4.0
- Architecture and main elements: smart sensor nodes and gateway
- ST sensors for industry 4.0
- STM32: 32-Bit MCUs and MPUs
- The benefit of edge processing and the role of AI
- Connectivity solutions
- Power management
- Current sense
- From CBM to PDM follow your path with ST solutions
- Design support hardware reference design and development kits
- Solution end to end
- Solutions for anomaly detection
