Driving Reliability Improvements Across the Enterprise

by , , | Jul 15, 2024 | Asset Management, Reliability | 0 comments

Emerson and AspenTech have advanced technologies on numerous fronts to help solve many challenges that manufacturers and producers face. One key area is in asset performance management to improve reliability. In an OPTIMIZE 24 Conference presentation, Enterprise Reliability Solution with Aspen Mtell and Emerson AMS, Emerson’s Greg Rome, and AspenTech’s Nithiya Parameswaran discussed ways to drive performance, resiliency, and sustainability improvements.

A significant challenge for organizations is a lack of skilled resources to improve maintenance practices. Skilled labor recruitment has become significantly more difficult as experienced practitioners leave the workforce. One way companies are addressing this shortage is to use cloud-enabled practices to enable experts to have a broader geographic reach.

Many manufacturers and producers seek to increase overall equipment reliability through IT/OT integration. Here’s a look at how these Emerson and AspenTech applications fit into the OT and IT integration architecture.

Greg described how AMS Machine Works delivers health data for rotating assets and their associated monitoring devices. AMS Device Manager provides real-time access to the health of a wide range of intelligent instruments and valves. Together, these feed their data streams to AMS Optics, enabling enterprise-level visibility & mobility to drive operational performance and workflow efficiency independent of location.

AMS Optics can also receive analytics from the numerous Plantweb Insight applications and Aspen Mtell. The Plantweb Insight data analytics software provides visibility into the health of key plant assets, and Mtell provides advanced pattern recognition using statistical and machine learning techniques to identify asset degradation. These applications help organizations move from traditional manual condition monitoring to automated asset monitoring.

Wireless intelligent field devices, such as the AMS wireless vibration monitor, play an essential role in providing the data for the analytics to turn into actionable information. The AMS Asset Monitor is an edge-based analytics solution with embedded prescriptive analytics to detect common issues associated with rotating machinery automatically. It can connect with AMS Machine Works and AMS Optics.

Aspen Mtell monitors asset health using a combination of monitoring technologies and artificial intelligence/machine learning (AI/ML) to detect early failure indicators. This enables predictive and prescriptive maintenance, boosting efficiency, reliability, and productivity.

Aspen Mtell provides early and precise warning with several monitoring methods—rules-based, conditions-based, first principle-based, AI/ML-based, and the ability to create custom monitoring algorithms. Data from IT sources such as Enterprise Asset Management (EAM) applications, process historians, and other OT sources are ingested and cleansed, analyzed by the appropriate monitoring algorithms, and turned into alerts, key performance indicators, and dashboards.

Boundless Automation is our vision for an industrial architecture built on a consistent, cohesive software ecosystem from intelligent field devices to the edge and the cloud—integrating operations to make all data instantly accessible, understandable, and usable for analytics, innovation, and performance improvement.

The AspenTech Inmation centralized data management solution combines the wealth of data and analytics from the asset performance and reliability domain with information and contextualization from other domains, such as production, safety, and sustainability. Optimizing operations requires insights across these multiple domains, powered by unified data access across the intelligent field, edge, and cloud.

Visit the links above for more information on these solutions to drive improved reliability and decision-making.

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The opinions expressed here are the personal opinions of the authors. Content published here is not read or approved by Emerson before it is posted and does not necessarily represent the views and opinions of Emerson.

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