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Mimir Analytics

Equipment machine learning at scale. Predict when your equipment will fail. Aspire to zero unplanned downtime.
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1 End Threshold Alarms

Mimir’s Anomaly Detection engine reviews all your equipment data 24/7 to flag issues across your fleet.

Instead of having simple threshold alarms (for example: “Temperature exceeds 60º”), Mimir account for all operating data ( for example: “Temperature outlier, accounting for ambient temperature, vibration, and frequency”). These “alarm boundaries” are continually evolving and improving as the models receive more equipment data.

2 Know Your Equipment Health

We apply cutting-edge machine learning methods to classify your equipment’s operation into one of many unobservable operating states.

By analyzing historical operating data and looking for patterns, our models can identify any number of normal operating and failure modes.

3 Prevent Equipment Failure

Our models have the ability to predict failures and prioritize maintenance across large equipment fleets.

The models have been able to achieve accuracies above 99% in predicting failures for upcoming budget cycles: improving maintenance, purchasing, and inventory decisions.

Request a quote and see how we can implement analytics models powered by machine learning into your equipment.