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Why Edge Devices are Essential to IIoT Applications

From reducing the amount of data that needs to be sent to the cloud for analysis to improving condition-based monitoring applications, edge computing devices are the local devices enabling an on-site industrial Internet of Things.

Charlie Norz

Digitalization in today’s global economy has become a necessity for modern manufacturing facilities. When running IIoT (industrial Internet of Things) applications, most—if not all—data needs to be collected, sorted, and analyzed in real time. To move between the cloud and local devices, an edge device is needed. These edge devices can transmit data between protocols used by local devices into the protocols used by the cloud. Instead of directly sending data to an off-site cloud to calculate analytics, edge devices can provide local execution of data analysis with low latency and a high level of determinism.

Data at the edge of the network can also be aggregated and contextualized to send rich, summary information directly to the cloud, ultimately reducing cloud data storage costs. Other edge computing benefits include condition- based monitoring, which can help prevent critical failures and downtime, as well as lower parts inventory and maintenance costs.

Another advantage to many edge devices is their use of the future-proof Linux operating system. Linux has been around for more than 30 years, and its acceptance has been growing exponentially. Used in most servers as well as in many military applications, it is robust and users can be confident that this open-source platform will continue to be available. Not having to update to a new platform every few years makes Linux-based edge devices ideal for innovative IIoT applications.

How to begin using edge devices
The first step in using edge devices is to find a business problem you are looking to solve. Instead of looking at the entire scope of the problem, try to break the issue down into small, manageable sections. Once you have done that, determine the priority of each—from highest to lowest.

The next step is to start collecting your plant floor data using containerized applications to analyze all the data. The benefit here is that both the connected worker on the plant floor as well as management can use the data to troubleshoot problems at the manufacturing level as they happen. It also helps off-site management look at efficiency, logistics, and other data to determine what is working, what areas need to be looked at more closely, and formulate plans for improvement on a long-term basis.

Depending on your industry, a good place to start may be your asset management program. If we look at this as an example, there are many pieces of key data that can be analyzed to help improve your company’s bottom line. These may include power consumption, vibration, bearing temperature, pressure, and uptime. Using this information, patterns can be recognized to determine causes of failure and what can be done to avoid those failures in the future. This can all done using edge computers to track and store data for delivery straight to the user when needed.

Wago’s edge approach
Wago combines the advantages of decentralized cloud computing with local control networks with our Edge Controller and Edge Computer. The Edge Controller is used to collect plant floor data information from industrial fieldbuses. If the application calls for it, these data can then be published directly to the cloud. If not, the Edge Computer can take the Edge Controller data, sort them and run analytics locally before posting to the cloud for anyone with proper access rights to see.

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