Across industry, cloud computing has been taking off for several years now due to its ability to offer end-users powerful analytics trained on large quantities of data without the need for expensive onsite information technology (IT) infrastructure. Despite this, aggregating and analyzing data as close to the point of data creation as possible is often preferred over offsite cloud analysis. In these instances, analytics is applied in real-time for faster analysis and to avoid sending data out of plants to limit the costs associated with data transmission bandwidth and offsite storage. Some companies also prefer onsite analysis at the edge to keep proprietary information within the four walls of a plant.
In response, hardware and software trends have emerged to facilitate a cloud-to-edge pipeline that allows companies to tap the benefits of cloud computing while keeping data and processing in-house whenever possible. On the hardware side, edge computing modules that provide in-plant intelligence capabilities have become more common.
Still, enabling edge technologies to perform what was once done largely in the cloud can be difficult without software containerization—a process that bundles an application’s code with related configuration files, libraries, and other required dependencies. Essentially, containers can be used to scale and deploy cloud-native applications on local edge computing systems.
Following from these trends, Emerson recently announced its PACEdge industrial edge platform, which the company says is designed to help accelerate digital transformation projects by enabling users to create and scale-up performance-boosting applications using machine data and open-source analytics code. By running the PACEdge platform on one of Emerson’s edge computers, end-users can deploy high-performance analytics as close as possible to the machines from which data is collected.
Through containerization, the PACEdge platform also allows developers and engineers to test their applications in a pilot environment comprised of only a few units, and then quickly scale up without worrying about compatibility issues or inconsistencies in the operating environment.
In related news, Emerson has also launched its RXi2-BP edge computer, which uses temperature management technologies to deliver a small-form factor edge computer for use in tight industrial locations.
“Many of today’s edge solutions offer limited connectivity and toolsets, making it difficult to extend across assets, machines or plants,” said Derek Thomas, vice president of marketing and strategy for Emerson’s machine automation solutions business. “The PACEdge platform provides a complete solution that enables manufacturers to start right at the machine with the connectivity and flexibility needed to scale up as they progress on their digital transformation journeys.”
To provide interoperable access to various field devices, control systems, IT systems, and cloud services, the PACEdge platform is compatible with multiple industry communication methods and protocols, including OPC Unified Architecture (OPCUA) and Message Queuing Telemetry Transport (MQTT). In addition, the software features drag-and-drop programming, embedded web interfaces, and data visualization capabilities that allow end-users to create custom dashboards to view operational metrics, such as overall equipment effectiveness (OEE), energy consumption, and sensor data. Data from external sources, such as weather forecasts and public utility rates, can also be implemented via machine learning algorithms to drive better decision-making and production planning.
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