In the Control Engineering webcast, “Edge series: Edge computing applications,” Jeffrey Allen, applications engineering manager at E Tech Group, and Nate Kay, control systems engineer at MartinCSI, explained how edge computing applications can be used for mission-critical, high-reliability automation and control applications. The webcast is archived for a year from the July 19, 2023, broadcast date.
- Understand how edge computing can benefits ERP, SCADA applications.
- Learn from how edge computing was applied in a chemical plant.
- Review the challenges and some other considerations related to edge computing.
Edge computing insights
- Edge computing can help enterprise resource planning (ERP) and supervisory control and data acquisition (SCADA) applications.
- Edge computing, as applied in a chemical plant, is providing benefits that can be replicated in other industrial edge computing applications.
- Challenges and some other considerations related to edge computing were covered in a July 19, 2023, Control Engineering webcast, archived for a year.
Edge computing is increasingly proving itself to be a powerful asset in enabling mission-critical, high-reliability automation and control applications. By allowing data to be processed as close as possible to where it is generated, edge computing enables faster processing, empowering operators to respond to changing production conditions in real-time. Moreover, it allows sensitive data to remain onsite, rather than being sent to the cloud for further analysis, thus increasing security while saving on wide area network (WAN) costs. These topics and others were discussed in a July 19 Control Engineering webcast, “Edge series: Edge computing applications.” The webcast featured Jeffrey Allen, applications engineering manager at E Tech Group, and Nate Kay, control systems engineer at MartinCSI, as speakers. A preview of some of the information covered is provided below.
Edge computing: ERP to SCADA applications
A common scenario in industrial facilities is for plant level operators to be required to input data from a business level Enterprise resource planning (ERP) into a supervisory control and data acquisition (SCADA)system that is directly connected to production assets. Traditionally, this is done via paper printouts, which change hands several times before being manually transcribed into a human machine interface (HMI) or other operator interface. While this process is highly secure due to the lack of digital data transfer from outside a plant’s local area network (LAN), it is labor-intensive and prone to human error. By contrast, via an edge computing device such as a local server, the information can be routed directly from an ERP to a local SCADA system in a controlled manner. “You can use the edge device as a traffic cop on these data connections to and from the ERP system or the cloud,” Allen said.
Edge computing chemical plant use-case
In one scenario shared by Kay, a chemical plant used a SCADA system to run its batching operation and recipe management processes. However, that information resided in a business-level ERP system, and had to be manually input to the SCADA from printed batch tickets. Because each system had its own proprietary crew managing and maintaining its software, allowing the systems to exchange data on their own would have required major modifications to each. To solve this issue, an edge device capable of translating the data was introduced to mediate between the two.
Edge computing: Challenges and other considerations
While the chemical plant use-case elaborated on by Kay had a marked return on investment due to the comparatively high expense that would have been incurred by modifying both the ERP and SCADA systems separately, Allen cautioned against using edge computing as a catch-all solution. For instance, in applications wherein an end-user or plant floor has many different systems, each of which would require an independent edge-device, implementation could become cost prohibitive. Therefore, it is important to carry out a full cost-benefit analysis before choosing to integrate an edge device.
KEYWORDS: Industrial edge computing
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