AspenTech: Optimizing Process Manufacturing
 
  • Aspen Mtell



    Aspen Mtell can recognize unique data patterns as predictions of future equipment behavior. Patterns are learned and then used to constantly monitor the real-time process to detect recurrences of the signatures.

      

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    The competition is excited about a 75% alert success rate. We're not.

    You need something you can rely on. Every Mtell message is a truthful, early, accurate forecast you can trust that delivers good prescriptive advice, helping you take affirmative action.
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    Get notified BEFORE the damage is done.

    Prescriptive Maintenance in Aspen Mtell® uses machine learning to prevent breakdowns, increase asset life, reduce maintenance costs and increase production output for any industrial process.
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    Share the knowledge.

    Learned behaviors (normal, degradation and failure) captured on one machine are readily transferred to equipment of the same type with the same sensor configuration. After a very short retraining period, every machine shares the same safety and breakdown protection.
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    Self-maintaining systems.

    When an anomaly is detected, Aspen Mtell dispatches alert notifications and requests for inspection. The results of inspection determines if the behavior is a failure signature or a new, normal operating state. The system trains itself to become smarter over time; learning and adapting to new asset operating conditions.
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