Preventive maintainance in IIoT
Download as PPTX, PDF0 likes115 views
The document discusses the importance of preventive and predictive maintenance within the Industrial Internet of Things (IIoT), highlighting various catastrophic failure examples and the advantages of leveraging advanced analytics for operational optimization. It outlines the components and architecture of a predictive maintenance system, including sensors and IoT devices that facilitate data collection and analysis. The conclusion emphasizes the necessity of smart predictions to prevent failures, inviting readers to learn more through the provided website.
Preventive maintainance in IIoT
- 1. Preventive Maintenance in IIoT
- 2. NY Transformer Explosion 28 Dec 2018 Brazil Dam Collapse 25 January 2019 California Wildfire November 2018 Catastrophic Failures
- 3. Why Predictive Maintenance?? An advanced analytics foundation to optimize operations & planning Ability to scour past data, identify patterns & model streaming data Opportunity to analyze real time field data Mine Recurring issues, failure indicators & resolutions A Robust, scalable solution which can integrate with other enterprise systems i
- 4. Predictive Maintenance IoT Components Sensor-As- A-Service Web 4.0 Gateway Edge Computing Predictive Analytics Cloud Computing
- 5. Humidity Sensor Sensors Magnetic RTD PT100 (left) & PZT Vibration Sensor (right) RTD PT100 sensor (400˚C)
- 6. Web 4.0
- 8. Integration & Testing Vibration Pattern Dominant Frequency Programmatically obtained the same dominant frequency along with other sensor data MQTT Endpoint
- 10. IoT Architecture Sensors and Actuators IoT Device IoT Device IoT Device IoT Gateway Communication Data Handling Data Handling Data Handling Device Management System REST Service – Data streaming Rules Engine SQL Analytics & Visualization Call Push SMS Email NOSQL GPRS WiFi 5G MQTT Http over REST BLEZigBeeRFZ-Wave Process Automation Resource mgmt Communications Process Automation Resource mgmt Communications Process Automation Resource mgmt Communications
- 11. Analytics on data (usecase 1): Distribution Transformers Electrical Signature Waveforms from vibration sensors Anomalies
- 12. Analytics on data (usecase 2): Smart Water Meters
- 13. Conclusion Predict Smartly, Don’t Fail By
- 14. Want to learn more? VISIT US AT: www.techolution.com Thank you