Predictive Maintenance for Fan Failures

In various industries, fan failures can significantly impact efficiency and effectiveness. Our partner acted as an AI consultant. They developed a special algorithm using acoustic sensors.

This algorithm helps to detect and predict fan problems. As a result, maintenance becomes easier and operations run smoothly.

The traditional approach of manually monitoring fans proved inadequate in preventing unexpected failures. Detecting failing fans in a large array was time-consuming and resulted in downtime and increased energy costs.

Our partner’s algorithm leveraged acoustic sensors to monitor fans in real-time. The algorithm can find fan failure early by analyzing sound patterns and locate where it happens in an array. Technicians can then replace individual fans without the need to shut down equipment.

Implementing AI consulting services and predictive maintenance solution has led to increased efficiency and reduced energy costs.

Important systems like pharmaceutical facilities, data centers, and food storage have experienced better reliability, reducing interruptions and ensuring efficient functioning.