Role of Cloud and Edge in Automation Architectures - Emerson Automation Experts

Role of Cloud and Edge in Automation Architectures

The Emerson acquisition of General Electric’s Intelligent Platform business closed on February 1, 2019. Emerson’s Rich Carpenter recorded a podcast with IoT Time’s Ken Briodagh the prior summer while serving as the General Manager of this business.

In the IoT Evolution podcast, IoT Time Podcast S.3 Ep.28 GE Automation & Controls, they discussed the Edge, Cloud, IIoT, and the changing architectures in Industrial Automation.

I’ll highlight a few of the points that Rich makes and invite to listen to 29-minute podcast.

In response to a question about “the Edge” and skepticism about its role, Rich noted that early in the advancement of the Industrial Internet of Things (IIoT), these computing devices primary role was to perform visualization of data from IIoT sensors. As computing power has increased with multi-core processors, Edge devices have assumed a great role to execute the learnings from Cloud-based analytics applications.

He shared an example of pump that moves water once per day. The Cloud-based apps could provide the optimum time when electricity was least expensive to perform this pumping but allow the edge device to perform the execution of this action based upon this information.

Rich explained that it makes sense to think of the Cloud-based apps as the learning piece of the puzzle and the Edge devices as the execution and optimization pieces. It’s not an either/or situation with the applications in Edge devices and in the Cloud. Both have their strengths. Effective information requires high-fidelity information which may exceed the bandwidth of pushing it all out to the Cloud.

Also, there is no guarantee that the communications between Cloud apps and Edge devices are always connected. Edge devices must have the information they need to operate autonomously.

He highlighted the use of Digital Twins for plant equipment reliability. Statistical models of the equipment are developed, and the data can be personalized depending on the operating environment. For example, even for the same compressor, the model for it running in the Saudi Arabian desert would be very different than the model of it running in cold climates or offshore oil & gas production platform.

Deterministic automation has been with us for decades. PLCs and DCSs make identical decisions based on the data coming in from the sensors. What IIoT is enabling is outcome optimizing control running advanced logic without affecting the deterministic control layer.

Listen to full podcast interview for more on Rich’s views in other areas including how business models are changing based upon the capabilities enabled by IIoT architectures.

Learn more about some of the automation & control products that are now a part of the Emerson portfolio of technologies that help improve business performance. You can also connect and interact with other machine automation experts in the PLC, PAC Systems & Industrial Computing Forum in the Control & Safety Systems group in the Emerson Exchange 365 community.

Posted Tuesday, August 20th, 2019 under Discrete and Industrial.

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