With an Industrial IoT platform, a diverse list of production assets become accessible for conducting remote inspections at any time.
• Performance and device health data monitoring
• Predictive maintenance
• Remote troubleshooting
• Smart alerts and notifications
• Security and access controls
Predictive Maintenance analytics helps to identify potential breakdowns before they impact production. Implementing predictive maintenance helps reduce downtime, optimize spare parts inventory, and maximize equipment life-cycle.
Key work flow to build Predictive Maintenance Proof of Concept (PoC):
The development PoC starts with Data Acquisition that describes the system in a range of healthy and faulty conditions. These raw data is pre-processed to bring it to a form from which we can extract condition indicators. These are features that help distinguish healthy conditions from faulty. We can then use the extracted features to train a machine learning model that can:
• Detect anomalies
• Classify different types of faults
• Estimate the remaining useful life-cycle of the machine
Finally, the algorithm deployed and integrated it into the system (i.e core control unit) for machine monitoring and maintenance.
Many industries are implementing predictive maintenance solutions so they can know ahead of time when a machine is about to fail and avoid costly breakdowns and lost productivity.
Predictive maintenance helps industries understand the condition of their equipment and identify potential breakdowns before they impact production.
Industrial IoT (IIoT) offers new levels of predictive maintenance to industrial enterprises.
Industrial IoT (IIoT) offers new levels of predictive maintenance to industrial enterprises. A digital twin or replica of physical assets, process or systems can be generated as models to predict preventive maintenance or to optimize output of complex machines or industrial process.
AWS Industrial IoT PaaS can be considered as potential platform to build and test PoC of various IIoT use cases. AWS IIoT platform provides complete virtuous cycle and build predictive maintenance models in the cloud and deploy at the edge. (Ref: https://aws.amazon.com/iot-core/features/)
With IIoT, industrial enterprises can assess the real-time health of diverse machinery such as wind turbines, blades, solar arrays, electrical power systems, fleet management, autonomous machinery, drones, actuators and more.