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Case Study
Manufacturing

Predictive Maintenance System for Smart Manufacturing

Client: Leading Automotive Parts Manufacturer
85%
Reduction in Unplanned Downtime
$2.1M
Annual Savings
40%
Longer Equipment Lifespan
99.2%
Prediction Accuracy
The Challenge

Unplanned equipment downtime cost the client $2.8M annually. Reactive maintenance meant replacing parts either too early (waste) or too late (production halts).

Our Solution

We deployed IoT sensor integration with a real-time ML pipeline for predictive maintenance — using time-series forecasting, anomaly detection, and a custom alerting dashboard for floor managers.

MLIoTPredictive AnalyticsManufacturing

“AirOxa's predictive maintenance system paid for itself in under 4 months. Our production uptime has never been higher.”

Raj Patel
Director of Operations, Leading Automotive Parts Manufacturer

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