Industrial IoT Edge Monitoring & Digital Twin Platform
Connecting 4,500 industrial robotic arms to predict mechanical failures 72 hours before breakdown.
Results
Reduction in catastrophic machinery breakdowns
Prevented unbudgeted emergency repair and idle labor costs
Advance notice given to maintenance teams before part failure
Real-time telemetry stream processed across 8 factories
The Challenge
Factory floor machinery breakdowns were costing $45,000 per hour in idle production lines. Sensor data was siloed and analyzed retrospectively rather than predictively.
Our Solution
We designed a ruggedized MQTT edge network with embedded TensorFlow Lite models streaming anomaly alerts to a central 3D digital twin dashboard.
How We Delivered It
Edge Sensor Gateway Mesh
Installed containerized edge runtime on industrial gateways capturing high-frequency vibration and heat signatures.
On-Device Anomaly Detection
Deployed micro-ML models evaluating sensor deviations locally without requiring continuous cloud connectivity.
Real-Time 3D Digital Twin Hub
Rendered live WebGL factory floor status enabling maintenance engineers to target failing bearings before line stops.
“Entecra turned our factory floors into intelligent, self-monitoring systems. The ROI was fully realized within the first 60 days of deployment.”
Technologies Used
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