Automotive Manufacturer: IoT Predictive Maintenance Platform
Deployed edge computing and ML models to predict equipment failures 2 weeks in advance, achieving 40% reduction in unplanned downtime and $8.5M in annual savings.
The Challenge
An automotive assembly plant with 500+ machines experienced 15% unplanned downtime, costing $50,000 per hour in lost production.
Our Solution
We implemented a comprehensive IoT platform with vibration, temperature, and current sensors on critical equipment. ML models trained on 5 years of failure data process 10 million data points daily.
Key Features Delivered
Results & Impact
Reduction in Downtime
Annual Savings
Prediction Accuracy
Advance Warning
“The predictive maintenance system paid for itself in 4 months. We now schedule maintenance proactively.”
Technologies Used
Services Provided
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