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Manufacturing
Predictive Maintenance Reduces Downtime by 60%
How an industrial manufacturer deployed IoT and AI to predict equipment failures, reducing unplanned downtime by 60% and saving $4.2M annually.
Client: Industrial Equipment ManufacturerDuration: 8 months
60%
Less Downtime
$4.2M
Annual Savings
85%
Prediction Accuracy
2,000+
Machines Monitored
The Challenge
Frequent unplanned equipment failures caused production delays costing $180K per hour. Traditional time-based maintenance was inefficient and reactive repairs were costly.
Our Solution
We deployed an IoT-enabled predictive maintenance system using 10,000+ sensors and ML models to forecast equipment failures 3-7 days in advance.
Key Results
Unplanned downtime reduced from 450 to 180 hours/year
Emergency repair costs reduced by 72%
Safety incidents related to equipment failure reduced by 90%
System ROI achieved in 14 months
Tech Stack
TensorFlowInfluxDBKafkaAWS IoTGrafana
"This predictive maintenance system has transformed our operations. We've cut unplanned downtime by 60% and our maintenance team now works proactively."
VP of Operations
Industrial Equipment Manufacturer
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