Because it is both equipment- and process-agnostic, Aspen Mtell can integrate and interoperate with almost all equipment and systems found in manufacturing including programmable logic controllers, distributed control systems, instrument systems, plant historians, management information systems, EAM systems, business systems and more to correlate patterns of failure that occurred in the past, before Aspen Mtell was installed.
The Aspen Mtell application collects equipment metadata from the EAM system to build the appropriate equipment hierarchy for monitoring, including mapping the sensor tag names to the correct equipment. Once set up, the system analyzes equipment work orders from the EAM system to correlate patterns of failure that occurred in the past, before Aspen Mtell was installed. Software Agents use the work order information to develop signatures of normal and failure modes, which are deployed immediately to monitor for the recurrence of those patterns, protecting against similar failures and detecting new anomalies that are readily categorized as either new normal conditions or new failure signatures. Unlike other systems, Aspen Mtell uses low-touch machine learning and adapts to new operating modes, enabling it to easily recognize new failure conditions.
Aspen Mtell’s Failure Agents initiate alerts to users, sending failure work orders with the exact failure code into the EAM system using machine-to-machine (M2M/Industrial IoT) technology. In this prescriptive maintenance process, the Agent prescribes appropriate maintenance activity based on the machine’s behavior. The operations and maintenance departments have an extended warning of the potential for failure and can work together with the other affected departments to make better decisions to remediate the failure in the most cost-effective way or adjust production. An Aspen Mtell notification allows small problems to be fixed before they become big ones.