
Through Aspen Mtell, Aspen Technology delivers a wide range of health‑monitoring capabilities, such as Emerson AMS threshold‑based condition monitoring, KPI‑driven calculations that turn sensor and original equipment manufacturer (OEM) data into quantifiable health indicators, and rule‑based multidimensional alerting. This functionality is complemented by multivariate statistical models and a configurable asset health score that synthesizes signals from all detection methods. Failure prediction is supported by pre‑built asset templates that use AI, physics‑based data and design curves to support anomaly detection, false positives reduction, and failure mode and effects analysis (FMEA). Users can build their own machine learning (ML) models through low‑code/no-code (LCNC) tools.
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