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Manufacturing Leads the Way to the Edge, Survey Confirms


Edge computing is paving the way to more effective automation and monitoring of industrial assets, systems, processes, and environments are increasingly important across manufacturing industries, including transportation, electronics, mining, and textiles.

When looking at edge computing progress across major industries, manufacturing is leading the way, a recent AT&T study concludes. The industry is taking full advantage of 5G and IoT technologies to “transform operations at the edge in groundbreaking ways, moving forward with initiatives such as smart warehousing, transportation optimization, intelligent inventory, and augmented maintenance,” the report’s authors state.

At this point, 78% of manufacturers globally are planning, have partially, or have fully implemented an edge use case, the study shows. In addition, 50% of manufacturers are at the mature stage of deployment for at least some of their edge network use cases.

“This puts manufacturing ahead of energy, finance, and healthcare verticals when it comes to edge adoption,” the AT&T report’s authors point out. “Among all the edge use cases, video-based quality inspection ranked the highest priority for manufacturers for full or partial implementation. It also was scored as one of the lowest in perceived risk.” These implementations involve a combination of IoT sensors and cameras “to pinpoint defects in real-time on the assembly line in order to discover root causes of defects more quickly, improve product quality, and reduce waste in the process.”

For example, as illustrated in the report, “a car manufacturer may use edge devices to watch a car as it traverses the assembly line, and if a windshield blade is not installed on one car because of variance in the windshield assembly, they can quickly review footage to find exactly how many cars were impacted by the issue. The carmaker can then fix the defects on each partially completed vehicle before they roll any further down the assembly line where the problem could be compounded, incurring rework, or waste at the end of the manufacturing process.”

See also: Manufacturing Ahead of the Curve via AI, 5G, and Edge

Edge computing is paving the way to more effective “automation and monitoring of industrial assets, systems, processes, and environments are increasingly important across manufacturing industries, including transportation, electronics, mining, and textiles. In order to implement safer and more productive practices, companies are automating their manufacturing processes with IoT sensors,” says Debraj Sinha, product marketing manager at NVIDIA, in a recent post. “IoT sensors generate vast amounts of data that, when combined with the power of AI, produce valuable insights that manufacturers can use to improve operational efficiency.”

Across many AI-inspection applications, edge computing “offers reduced bandwidth, lower latency, and proximity of data,” the AT&T report’s authors note. “The power of edge makes it possible to do this across multiple, global facilities, effectively handling the large number of files and formats typically found in a modern manufacturer’s workflow.” The AT&T report’s authors also add a word of caution, noting that while the manufacturing industry “isn’t typically thought of as the target for cyberattacks, but as we continue down the path towards tech transformation, cybersecurity is increasingly important as a priority.”

Kevin L. Jackson, author and CEO of GC GlobalNet, echoes these concerns in a recent article, noting that the rise of remote work over the past two and a half years “uncovered the industry’s complacency in adopting many network technology-enabled efficiencies and the necessary cybersecurity protections. It also shines a light on the importance of real-time data. These massive supply chain disruptions not only highlighted a lack of supply chain visibility but the industry’s inability to respond to changes in customer demand. Smart manufacturing really demands greatly improved supply chain visibility and the ability to sense consumer demand changes. Supply chain managers historically have looked to the past to try to plan for the present, but that doesn’t work in today’s world. You have to really sense what’s happening now in order to respond, reduce risk and increase efficiency.”

The business case for edge computing is compelling for many reasons, as it “helps manufacturers increase quality while simultaneously reducing their costs operationally,” Jackson states. In addition, it provides opportunities for manufacturers to “reduce their bandwidth requirements and lower network latency. Data proximity advantages can also be used to employ artificial intelligence inspection across multiple facilities in a very consistent and cost-effective manner.”

The shift to edge “is taking smart manufacturing to a new level,” Jackson writes.


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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