
A manufacturing company with 12 production facilities wanted to implement IoT sensors to monitor equipment health, optimize energy usage, and improve production efficiency. Edvirra designed and deployed an end-to-end IoT solution connecting 8,500 sensors across all facilities.
We started by identifying critical equipment that would benefit most from IoT monitoring - production machines, HVAC systems, and quality control equipment. We selected sensors for temperature, vibration, pressure, and energy consumption. Each sensor connects to edge gateways that process data locally before sending to the cloud.
The architecture uses AWS IoT Core for device management and message routing. Data flows from sensors to edge gateways, then to AWS IoT Core, and finally to a time-series database (InfluxDB) for analytics. We built dashboards using Grafana that show real-time equipment status, alerts for anomalies, and predictive maintenance recommendations.
Machine learning models analyze historical data to predict equipment failures 2-4 weeks in advance. This allows maintenance teams to schedule repairs during planned downtime instead of emergency shutdowns. The system also optimizes energy usage by automatically adjusting HVAC and lighting based on occupancy and production schedules.
After 6 months of operation, the factory has achieved:
30% reduction in unplanned downtime
22% decrease in energy consumption
15% increase in overall equipment effectiveness