Manufacturing AI Overhaul
The Challenge
A major manufacturer was experiencing 40% unplanned downtime across 12 production lines, costing millions annually. Legacy SCADA systems couldn't predict failures, and maintenance was entirely reactive.
Our Approach
We deployed IoT sensors across all production lines and built custom ML models trained on 18 months of historical failure data. The system integrates directly with existing SCADA infrastructure via OPC-UA.
The Solution
A real-time predictive maintenance platform that monitors vibration, temperature, and pressure data from 200+ sensors, predicting equipment failures 48-72 hours in advance with 94% accuracy.
The Results
40% reduction in downtime
Unplanned downtime dropped from 15hrs/week to 9hrs/week across all lines.
$2.4M annual savings
Avoided emergency repairs and production losses.
94% prediction accuracy
ML model correctly identifies failure events before they occur.
6-month payback
Full ROI achieved within the first two quarters.
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