Manufacturing Leads the Way to the Edge, Survey Confirms


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

Manufacturing leads the way when looking at edge computing advances across key industries, according to a recent study by AT&T. The industry is taking full advantage of 5G and IoT technologies to “transform operations at the edge in game-changing ways, driving initiatives such as smart warehousing, transportation optimization, smart inventory and advanced maintenance,” according to the report’s authors.

The study shows that 78% of manufacturers worldwide are currently planning, have partially or fully implemented an edge use case. Additionally, 50% of manufacturers are in the mature deployment phase for at least some of their edge network use cases.

“This puts manufacturing ahead of the energy, finance and healthcare industries in terms of edge adoption,” the AT&T report authors point out. “Of all edge use cases, the video-based quality check for manufacturers has the highest priority for full or partial implementation. It was also rated as one of the lowest perceived risks.” These implementations include a combination of IoT sensors and cameras “to locate defects in real-time on the assembly line to discover the root causes of defects faster, improve product quality and reduce waste to reduce”.

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Download the infographic now: Views from leading manufacturers on Edge Computing and 5G

For example, as outlined in the report, “an automaker can use Edge devices to watch a car as it traverses the assembly line, and if a windshield blade is not installed on a car due to windshield assembly variances, they can do quickly review the footage to find out exactly how many cars were affected by the problem. The automaker can then fix the defects on any partially completed vehicle before it rolls further down the assembly line, where the problem could worsen, rework, or create waste at the end of the manufacturing process.”

See also: Manufacturing ahead of the curve with AI, 5G and Edge

Edge computing paves the way to more effective “Automation and monitoring of industrial assets, systems, processes and environments is becoming increasingly important across manufacturing industries, including transportation, electronics, mining and textiles. To implement safer and more productive practices, companies are automating their manufacturing processes with IoT sensors,” said Debraj Sinha, product marketing manager at NVIDIA, in a recent post. “IoT sensors generate massive amounts of data that, combined with the power of AI, provide valuable insights that manufacturers can use to improve operational efficiencies.”

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For many AI inspection applications, edge computing offers “reduced bandwidth, lower latency, and proximity to data,” the AT&T report authors note. “The power of Edge makes it possible to do this across multiple global facilities and effectively handle the large number of files and formats typically found in a modern manufacturer’s workflow.” The authors of the AT&T report also add A word of caution, noting that while the manufacturing industry is “not typically viewed as a target for cyberattacks, cybersecurity is becoming increasingly important as we move toward technological transformation.”

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 “reveals the industry’s complacency in embracing many of the efficiencies enabled by network technology has necessary cyber security precautions. It also sheds light on the importance of real-time data. These massive supply chain disruptions highlighted not only a lack of transparency in the supply chain, but also the industry’s inability to respond to changes in customer demand. Smart manufacturing truly requires vastly improved supply chain visibility and the ability to anticipate changes in consumer demand. Supply chain managers have historically looked to the past to try to plan for the present, but that doesn’t work in today’s world. You have to really feel what’s happening to be able to react, reduce risk and increase efficiency.”

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The business case for edge computing is compelling for many reasons, as it “helps manufacturers improve quality while lowering their operational costs,” explains Jackson. In addition, it offers manufacturers opportunities to “reduce their bandwidth requirements and reduce network latency. The benefits of data proximity can also be leveraged to deploy artificial intelligence inspections across multiple facilities in a very consistent and cost-effective manner.”

The move to Edge “takes intelligent manufacturing to a new level,” writes Jackson.





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