In this case study, we delve into the challenges faced by the customer when it came to identifying and addressing journal bearing vibration increases. Traditional threshold-based alarms proved inadequate, either triggering too close to failure or generating an excessive number of false alarms. This created a pressing need for a more sophisticated approach that could provide early warnings without overwhelming the maintenance team.


Learn how AI Expert’s early detection and recommendations for journal bearing vibrations saved an enterprise $10,000 in unplanned downtime.


Download the case study to know how AI-powered predictive analytics can do wonders for your asset performance & predictive maintenance strategy.

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Don’t take only our word for it

Companies using UptimeAI are saving millions with timely alerts & near-zero downtime

“We were monitoring limited equipment in isolation. UptimeAI’s approach enables us to look at the interrelations & scale the plant”– Oil & Gas, Executive Asia

“Building a full plant monitoring application on an IoT platform is too difficult. In contrast, ‘AI Plant Expert’ offers higher ROI & quick scale-up with an out-of-box, comprehensive solution.”– Power, CIO Asia