Case Study Snippet: Sensor Fusion Identifies Mechanical Degradation in Sinter Fan Before Failure
June 8, 2025
By Razor Labs
5 min read
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June 8, 2025
At a leading alloys production site, DataMind AI™ flagged early signs of mechanical degradation in a critical sinter fan – well before any traditional system raised concern.
By analyzing subtle vibration behavior using sensor fusion and multi-signal inputs, the platform pinpointed a misaligned coupling and impeller imbalance caused by a partially unsealed suction cowling and historical impact damage.
Conclusion
This early insight enabled the team to act before failure occurred – avoiding 7 hours of unplanned downtime, preventing costly equipment damage, and saving an estimated $336,000. A clear example of how predictive AI helps protect operational reliability and reduce maintenance risk.
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