When operating a factory, one of the major goals is to

minimize issues, downtime, or anything else outside the status quo and ensure

smooth operation. However, this is easier said than done, as all machines require

maintenance and must contend with unforeseen failures. Predictive maintenance is

emerging as a powerful tool that leverages AI and machine learning to better

understand when and where maintenance is required to minimize downtime and preemptively

handle issues before they become catastrophic.

In this episode, host Spencer Acain is joined by Dr. James

Loche, Head of Research for Senseye Predictive Maintenance, to explore the unique

approach Senseye is taking to the problem of keeping factories running as

smoothly as possible.

In this episode you will learn:

·        

What is Senseye (2:40)

·        

Senseye as a decision support system (4:30)

·        

How AI brings flexibility and scalability to

predictive maintenance (11:04)

·        

Monitoring operations vs. looking for failures

(13:13)