[caption id="attachment_6740" align="alignnone" width="1200"]Edge Computing phoenixNAP[/caption]

IBM defines Edge Computing as a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. Besides helping to unlock the potential of the massive data generated by connected devices, edge computing helps to deliver faster insights, improved response times, and better bandwidth availability.

The origins of this technology can be traced to the 1990s when Akamai Technologies Inc. introduced its first content delivery network to alleviate Internet bottlenecks. This network featured nodes placed at locations geographically closer to the end-user that stored cached static content such as images and videos. In 1997, computer scientist Brian Noble demonstrated how mobile technology could use edge computing for speech recognition. Fast forward to now; this technology is extensively used to address the data boom, which is challenging for cloud and AI alone. Thanks to edge computing data processing and analysis are done closer to the source point. While this has reduced latency, with the rollout of 5G, edge computing is expected to gain full momentum and revolutionize industries. End users do not have to rely on cloud availability to draw insights from data using machine learning algorithms. Currently, this technology is employed in various manufacturing sectors too.

With edge devices, such as sensors and actuators, edge computing is set to be a crucial part of the Industrial Internet of Things (IIoT) equation to accelerate digital transformation. Management consulting firm, McKinsey & Co., predicts that the Industrial Internet of Things (IIoT) will create US$7.5 Trillion in value by 2025. There are more plus sides to this technology. This includes lesser costs due to the elimination of networking equipment (switches, routers, servers) and minimal dependency on associated cloud services, better and improved execution of computational power in smaller footprint devices, and faster access to temporal data for real-time analytics. These are the reason why edge computing is popular in manufacturing plants.

Craig Resnick, a vice president at the ARC Advisory Group, says “In terms of manufacturing applications, edge computing has only started being deployed for about five years or so.” He adds, “However, its usage is steadily increasing for automation equipment by manufacturers in many industries. The implementation of edge computing is evolutionary rather than revolutionary, but you will begin to see applications in most plants in just a few years.” “Quick acquisition and processing of data, as well as secure data storage, are definite advantages of edge computing over cloud computing in select applications,” notes Resnick. This is true as less reliance on the cloud for storing, computing and transmitting data, free the network, and cloud space.

Not only that, but the benefit of edge computing is also about its ability to achieve predictive maintenance on an assembly line or throughout a plant. The installed sensors aid in continuous monitoring of machine health and identify signs of time-sensitive maintenance issues in real-time. This data is then analyzed on the assembly line, enabling managers and workers to execute remedial actions on machines much earlier before they stop working and halt production. Besides preventing costly plant shutdowns, preventive maintenance helps companies prolong the useful life of machines.

“The edge computing can improve both process and product quality. It also offers effective asset management and tracking,” says Scott McClelland, vice president of product management and engineering at Harting Inc. of North America. He explains that the manufacturing process generally comprises of multiple machines. When data is relayed from the combined machines and devices, it helps a manufacturer improve how the process is performed at each step, and the quality of the final product.

McClelland says, “As for asset management high-value parts, raw materials and tooling or molds can be equipped with location-type sensors or RFID tags (that act as sensors), so these items are easy to locate in the plant. The same sensors can even be placed on parts for immediate location status as they move through the production process.”

When coupled with cloud environments, edge computing establishes a hybrid edge-cloud infrastructure which is called as IT (information technology)-OT (operational technology) convergence. This pairing up has a two-way advantage, i.e. data, log records, and application information created at the edge is tied to cloud and vice-versa. This ensures better data protection and security, and production continuation, especially in case the cloud temporarily becomes unavailable for some reason. This allows manufacturers to build a sturdy framework for full enterprise security, regulatory fulfilment and audits, with high operability among multiple plants.