Manufacturing leads the way to the edge, survey confirms

Edge computing paves the way for more efficient automation and control of increasingly important industrial assets, systems, processes, and environments across manufacturing industries, including transportation, electronics, mining, and textiles.

When looking at the advances of edge computing across major industries, manufacturing is the most recent leader AT&T Study Concludes. The industry is taking full advantage of 5G and IoT technologies to “transform operations at the edge in pioneering ways, and advance initiatives such as smart storage, transport optimization, smart inventory, and enhanced maintenance,” the report’s authors stated.

At this point, the study shows, 78% of manufacturers globally are planning, partially implementing, or fully implementing an advanced use case. Additionally, 50% of manufacturers are in the maturity stage of deploying at least some edge network use cases.

The authors of the AT&T report note that “this puts manufacturing ahead of the energy, finance, and healthcare sectors when it comes to cutting-edge adoption.” “Among all edge use cases, video-based quality inspection ranked first in the manufacturers’ priority ladder for full or partial implementation. It also scored as one of the lowest perceived risk.” These applications include an array of IoT sensors and cameras “to identify defects in real time on the assembly line in order to discover the root causes of defects faster, improve product quality, and reduce waste in the process.”

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For example, as explained in the report, “A car manufacturer may use sophisticated hardware to watch a vehicle cross an assembly line, and if a windshield blade is not installed on one vehicle due to a discrepancy in the windshield assembly, it can quickly see the screenshots for the number of vehicles Exactly affected by the problem. The automaker can then fix the defects on each partially completed vehicle before they roll down the assembly line where the problem can be exacerbated, incurred rework, or wasted at the end of the manufacturing process.”

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

Edge computing paves the way for “the automation and control of increasingly important industrial assets, systems, processes, and environments 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,” As Dibraj Sinha, Director of Product Marketing at NVIDIA, says in a recent report Mail. “IoT sensors generate massive amounts of data that, when combined with the power of artificial intelligence, produce valuable insights that manufacturers can use to improve operational efficiency.”

The authors of the AT&T report note that, across many AI screening applications, edge computing “provides low bandwidth, lower latency, and closer proximity to data.” “The power of the edge makes it possible to do this across a multitude of global utilities, 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 usually seen as a target for cyberattacks, as we continue down the path toward technological transformation, cybersecurity is becoming increasingly important as a priority.”

Kevin L. Jackson, author and CEO of GC GlobalNet, has been repeating these concerns recently Article – Commoditynoting that the emergence of remote work over the past two-and-a-half years “revealed the industry’s laxity in embracing many of the competencies that support networking and protection technology essential to cybersecurity. It also highlights the importance of real-time data. These massive disruptions in the supply chain have yet to highlight Highlighted only the lack of supply chain visibility but the industry’s inability to respond to changes in customer demand.Truly intelligent manufacturing requires a dramatically improved view of the supply chain and the ability to sense changes in consumer demand.Source chain managers have historically looked to the past to try to plan for the present, but this does not It works in today’s world. You have to really feel what is happening now in order to respond, reduce risk and increase efficiency.”

The feasibility study for edge computing is compelling for several reasons, as it “helps manufacturers increase quality while simultaneously reducing their costs in operational terms,” ​​says Jackson. Additionally, it provides opportunities for manufacturers to “reduce bandwidth requirements and reduce network latency. The advantages of data proximity can also be used to employ AI scanning across multiple facilities in a highly consistent and cost-effective manner.”

Jackson writes that shifting to the edge “takes smart manufacturing to a new level.”

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