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Managing Manufacturing ‘On The Edge’

Edge solutions are a nascent trend that will continue growing to enable digital transformation in every industry and integral to the implementation of Industry 4.0 in manufacturing. Digital transformation necessitates extending and distributing the digital enterprise to the edge and connecting everything and everyone digitally. Over the next several years, edge solutions will experience growth, growing pains and evolution in the trend itself according to a report from Gartner.

Edge Computing Evolution

There are several factors driving edge computing, but latency has been the primary driver to date. The rapid increase in data production at the edge will shift the balance to reducing bandwidth costs by bringing more compute power closer to the point of data production. Likewise, data and compute power will increase the use of deep learning across a broad array of edge applications.

The growth of IoT and the shift from air-gapped operational technology to networked edge devices will create a massive challenge to extend enterprise security to newly connected edge devices. Connectivity itself will also be a challenge. Expectations that cellular connectivity (and 5G) will meet enterprise requirements are set far too high according to the Gartner report.

Diverse use cases are driving the interest in edge capabilities for data and analytics. These range from supporting real-time event analytics for system automation, control and maintenance, to immersive experiences, to enabling autonomous behavior of ‘things’. An increasingly popular use case is computer vision, where the capture of streaming data and inferencing on it often must occur at or very near distributed assets. With more digitalization of interactions and more instrumentation of assets at distributed customer touchpoints, the volume of data created and processed at the edge is exploding. Unlike traditional data centers and enterprise applications, edge computing digitizes everything — and lots of this edge data is ephemeral. It has a very short half-life of value, and may never leave the edge. It will be created and possibly stored, processed, analyzed and destroyed without ever being collected in a data center or the cloud.

By using distributed computing resources and spreading the load across the ecosystem, the enterprise can more broadly scale its capabilities and extend the impact into more areas of the business. This includes use cases and outcomes traditionally managed only via operational technology teams, such as those managing equipment in industrial settings. Pushing data management capabilities toward edge environments can also bring benefits in the form of greater fault tolerance and autonomous behavior. If edge environments do not require centralized resources, then issues with connectivity to or unplanned downtime of those centralized resources don’t disrupt processes that rely on local edge capabilities.

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