Predictive Maintenance for Industrial Equipment

Built a predictive maintenance platform monitoring vibration, temperature, pressure, and performance metrics from industrial equipment. Machine learning models predict equipment failures 5-7 days in advance with 87% accuracy, enabling scheduled maintenance and preventing unplanned downtime. Reduced maintenance costs by 25% and increased equipment uptime to 98.2%.