Industrial Equipment

Remote Monitoring with Real-Time Insights

IoT Sensor Applications For Industrial Equipment

Equipment Monitoring

Monitor critical equipment for status looking at vibration, temperature, noise and leaks.

Conveyors and Transfer Equipment

Vibration, temperature, noise and leaks, leak detection and other sensors are installed in the conveyor transfer equipment. Out of limit sensor reading trigger a message to manufacturing service.

Manufacturing Product Status

Monitor the actual product being manufactured for temperature, noise and vibration. This information can be recorded and sent wirelessly for review and analysis.

The Solution: Remote Machine Monitoring with Real-Time Insights

This solution solves the complexities of plant infrastructure management. Sensors are installed in key areas that monitor equipment up-time, product delivery counts, replenishment needs and even cleaning cycles. Allowing constant data communication on various parameters. Anomalous sensor data trigger alarms to facilities management. These early warning signals minimize equipment downtime and ensure smooth flow of operations.

Benefits
  • Better system optimization
  • Scheduled maintenance
  • Longer system usage
  • Minimize downtime
Target Application
  • Industrial Machines
  • Transfer Equipment
  • Process and Quality Improvement
  • Warehousing

Embedded Planet epSensors: Sensors include temperature, proximity, position, moisture, flow, fluid leaks and vibration.

Embedded Planet epGateway™: Sensors connect directly to the Embedded Planet epGateway. The epGateway serves as a sensor hub for both wired and wireless sensors including epSensors. The epGateway can send data to Microsoft Azure, IBM Cloud and Amazon AWS. It also provides remote device management in a secure multi-tenant environment.

epCloud: Sensor data is sent to Microsoft Azure, IBM Cloud and Amazon AWS. Device management is performed via epCloud and can securely update device firmware and manage the system remotely. Data rendered into visualization dashboards which use rules to notify maintenance personnel via texts or push the data to tools for automatic work order creation. Data is stored in a cloud-based database for longer term historical analysis which is required for predictive analytics.

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