MxD — in a new series of articles — scans the landscape of technologies and trends fueling manufacturing’s ongoing digital transformation: What’s here? What’s coming? And what’s the impact, including on the workforce? For this story we take a look at edge computing, featuring insights from Google Cloud’s Manufacturing Industry Manager Fabien Duboeuf and Mike Ensor, Google Cloud’s Technical Lead for Distributed Cloud Solutions.
At MxD, Google Cloud shares factory floor space with Betacom and Ingram Micro. There, interactive demonstrations include one with ClearObject, which runs its artificial intelligence (AI) software on Google Distributed Cloud (GDC) edge hardware. The demonstration was among topics explored in a recent MxD webinar, “Delivering Modern Manufacturing Outcomes with AI at the Edge,” with panelists including Duboeuf.
Here’s more on edge computing:
Why edge?
Edge computing, which is done at the “edge” of a network — or as close as possible to a data source — is helping manufacturers address challenges ranging from labor shortages to quality control. When combined with generative AI, edge computing allows manufacturers to take action quickly on the real-time feedback they are getting from equipment data, says Google Cloud’s Manufacturing Industry Manager Fabien Duboeuf. That’s essential, Mike Ensor, Google’s Technical Lead/Distributed Cloud Solutions added, because manufacturers are on “razor-thin” timelines. Sending real-time data to centralized cloud servers is no longer a complete answer because latency issues can mean costly delays, he said. Edge complements — or extends — the cloud.
Why now?
The growing need for faster and more efficient data processing and the proliferation of internet of things (IoT) devices have been key to adoption of edge computing. Hastening that pace, Ensor noted, is that IoT is rapidly evolving. Manufacturers, he said, are moving beyond the idea of sensors just collecting data and focusing on how that data can be used in areas such as predictive analysis. Edge computing paired with private 5G, Duboeuf added, is enabling manufacturers to translate insight about what’s happening at the equipment level to a worker “who could have started a week ago.” “With that knowledge,” he added, “what they’re gaining is agility and speed.” Edge computing can also help boost cybersecurity by keeping data off of centralized cloud servers. This is a crucial consideration for manufacturing, which continues as the top target for cyberattacks.
How quickly is edge computing growing?
Recent research forecasts that the edge computing industry will be worth $110.6 billion by 2029. However, experts continue to see uneven adoption among small and mid-size manufacturers. Manufacturers that don’t have cash for a large-scale smart-factory investment end up cobbling systems together themselves, Ensor said, adding: “Those are the organizations that are largely getting left behind.”
What about workforce impact?
As manufacturing becomes more technical, the industry is attracting fewer qualified workers. That workforce gap is “driving a lot of the edge adoption,” Ensor said. Reasons for that include the ability of edge-enabled real-time monitoring and optimization of processes to increase efficiency and reduce the need for manual intervention. “We have to use edge computing to alleviate a lot of the toil and automate the areas that are difficult for humans to do,” he added.
Other headlines? Google Cloud is taking McDonald’s to the edge. McDonald’s plans to rely on Google Cloud technology in thousands of its restaurants around the world, with the company saying it will use edge computing capabilities to “draw new insights into how equipment is performing and enact solutions that reduce business disruptions.” “Quick-serve restaurants,” Ensor added, “are very manufacturing oriented.”
