When predictive diagnostics meet expert analysis, even the most subtle warning signs can prevent major disruptions. In this case, SMARTdiagnostics DeskAI machine learning model flagged an anomaly in the exhaust system’s fan shaft, prompting a deeper investigation. What followed was a collaborative effort between data and vibration expertise that uncovered a hidden mechanical failure before it could trigger costly unplanned downtime. Here’s how the team turned insight into action, saving time, money, and operational confidence.
Using this data, a SENTRYsolutions analyst recommended looking into if the fan was being started or ran differently on that day versus others and recommended inspecting the bearing for lubrication, to rule out more common causes. When the customer reported that the bearing was greased regularly, it was clear something deeper was occurring.
Upon inspection, despite regular greasing, a retainer ring had failed, causing the bearing to seize. With this knowledge in hand, the team was able to perform a repair at the next scheduled downtime. Proactive action prevented four hours of unplanned downtime, resulting in more than $450,000 in savings.
