As process manufacturing scope and capabilities have grown over the decades, so, too, has the need to carefully deploy and monitor dozens, hundreds, or even thousands of automation assets. Plant personnel rely on measurement and analytical instrumentation, digital valve controllers, wireless devices, and more to help them ensure processes are optimized and to keep operations safe, efficient, and effective.
As plant adoption of smart devices has expanded, desire has increased for a near-instantaneous way to deliver the resulting data to analytics, dashboards, machine learning, historians, and other applications.
As organizations began to digitally transform their operations to meet modern needs, this deployment of assets was no longer limited to a single plant. Operations grew as crews simultaneously shrank, and, as a result, more centralized teams found a need to effectively deploy and monitor standardized equipment across the enterprise. Keeping track of configuration, records, workflows, and guidelines in those circumstances was no longer possible on paper. As a result, maintenance and reliability teams have long relied on asset management software like AMS Device Manager to provide enterprise-wide visibility into the data, health, and key analytics of intelligent field devices.
More systems means more complexity
Today, that operations, maintenance, and reliability ecosystem is becoming even more complex. Organizations are expanding their range of enterprise applications to adopt a wide variety of analytics, historians, machine learning, and advanced modeling to further break down silos and benefit from historically underused or inaccessible datasets. The information locked away in these siloed systems, when coupled with Industry 4.0 technologies, can often be the key to unlocking the most evasive efficiency gains—the ones that drive competitive advantage.
Making the connections to that wide array of critical third-party systems is often a difficult task. Typically, each third-party system connected to an asset management solution requires its own complex custom data integration, which takes time and deep expertise. These connections are also fragile, as they can be interrupted by system updates on either end, making them particularly difficult to maintain.
“Today’s process manufacturers are embracing analytics, machine learning, dashboards and other advanced analysis techniques and applications to help consolidate fragmented data sets that have been historically overlooked and underutilized.” – Anna Veleña, Emerson
“Today’s process manufacturers are embracing analytics, machine learning, dashboards and other advanced analysis techniques and applications to help consolidate fragmented data sets that have been historically overlooked and underutilized.”
– Anna Veleña, Emerson
A common binding
Fortunately, modern asset management data solutions like Emerson’s new AMS Device Manager Data Server make it easy to publish (in near-instantaneous manner) critical asset data into Emerson software tools as well as other common dashboarding tools and applications like Microsoft PowerBI, AspenTech’s Aspen MTell and Inmation software, plant historians, and many others. AMS Device Manager Data Server uses MQTT, a lightweight network protocol to send device data outside the control network into third-party platforms for analysis and insight.
AMS Device Manager Data Server enables users to replicate their AMS Device Manager data outside the process control network into industrial analytics and information management systems and software like Aspen Mtell, AspenTech Inmation, and others via MQTT lightweight standard messaging protocol.
Not only do these solutions help support organizations’ digital transformation initiatives, but they form the foundation for a more centralized model of maintenance and reliability deployment. The secure infrastructure is as easily accessible remotely as it is on-premises, increasing usage for monitoring and optimization activities and more easily empowering small teams with remote monitoring across the enterprise. Additionally, the tools foster increased data and usability across teams and organizations – from the field to the boardroom and everywhere in between.
To learn more about how AMS Device Manager Data Server can help you level up your analytics, machine learning and digital transformation initiatives related to smart devices, visit the AMS Device Manager Data Server page at Emerson. And while you’re here, please drop a note in the comments to share your own strategies for aggregating and analyzing data across the enterprise!
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