When NexGen Manufacturing approached us, they had a problem common to large industrial operations: 15,000 IoT sensors generating data across 12 facilities, but no real-time visibility into equipment health. Maintenance was reactive, costly, and disruptive.
The Challenge
NexGen's existing setup involved multiple disconnected monitoring tools, each covering different equipment types. Data was collected in batches, analyzed overnight, and reviewed the next morning. By the time a problem was identified, it had often already caused downtime.
The CloudIQ Solution
Phase 1: Unified Data Ingestion
We deployed CloudIQ's protocol-agnostic gateway to ingest data from all sensor types - vibration, temperature, pressure, humidity - into a single real-time data pipeline. No sensor replacement needed.
Phase 2: Edge Analytics
Critical anomaly detection was moved to edge devices, reducing latency from minutes to milliseconds. Equipment showing early signs of failure triggered immediate alerts, not next-day reports.
Phase 3: Predictive Models
With six months of clean, structured data, we trained predictive maintenance models that forecast equipment failures 2-4 weeks in advance with 92% accuracy.
Results
- 60% reduction in unplanned downtime
- $2M annual savings in maintenance costs
- 99.9% platform uptime across all facilities
- ROI achieved within 5 months of deployment