Predictive Maintenance System

The Challenge

Unexpected equipment failures were causing costly production downtime. Preventive maintenance schedules were either too aggressive (wasting resources) or too lenient (missing failures).

Our Solution

We deployed IoT sensors across critical equipment and built ML models to predict failures based on vibration, temperature, and usage patterns. The system alerts maintenance teams 2-3 weeks before predicted failures.

Results

• Unplanned downtime reduced by 75%
• Maintenance costs reduced by 30%
• Equipment lifespan extended by average of 2 years
• Production efficiency increased by 18%