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A slide from a SkillReal presentation shows the digital twin at left and the company’s inspection photo. (SkillReal)

SkillReal says inexpensive camera and AI add up to faster, better inspections

SkillReal uses off-the-shelf light cameras and its own algorithm to drastically speed up inspections currently done by slow humans or expensive equipment.

A company says that its digital twin alignment system, incorporating a sophisticated AI algorithm and an off-the-shelf camera, has the potential to revolutionize the auto industry, potentially saving it up to a staggering $20 billion in the effort to detect defects on the manufacturing line.

Generally, such inspections of spot welds, bolt holes and the like are handled one of three ways:

  • Slow manual inspections that can have high error rates.
  • Even slower inspection with coordinate-measuring machines (CMMs) that can take hours to inspect 150 spot welds.
  • Tremendously expensive technology, such as lasers, that still aren’t perfect.

SkillReal, an Israeli company that just exited stealth mode after proving its technology at Volkswagen’s Wolfsburg plant, says that using a roughly $1,000 camera and a gaming laptop, its software can compare a photo of a part with a digital twin, highlight problems and be completed in mere seconds.

That’s in contrast with what some OEMs and suppliers do, which is essentially hand an inspector a Sharpie and a PDF showing weld locations and other features. The inspector then visually compares them and marks the part for deficiencies.

Pete Grabowski, SkillReal’s chief operating officer at its North American headquarters in Livonia, Michigan, said the costs of these inspections can really add up because of OEM demands involved in safe launches, in which suppliers are made to pay up to $50,000 a month to third-party companies to ensure parts meet OEM and any regulatory standards. That adds up quickly when a supplier has dozens or hundreds of parts going to multiple vehicle programs.

He said that what sets SkillReal’s system apart is not just detecting features represented in a CAD that have an XYZ coordinate, but how accurate the system is. “We can pinpoint the exact location of those features with submillimeter accuracy. And we do that in seconds.” The system is forgiving, too, able to account for positional variations of the photographed test object. One test of the system that Grabowski called “our John Henry versus the machine” was conducted at a Detroit area stamping and assembly plant. The test pitted SkillReal against the plant’s best marker auditor in a daunting challenge: evaluating welds and other items on the entire underbody of a vehicle involving multiple photos. The plant’s operator finished in 90 minutes. “We were done in less than 10,” Grabowski said.

At the VW plant in Wolfsburg, the results were even more dramatic. Grabowski said VW had two operators working entire eight-hour shifts checking spot welds, while SkillReal’s software covered the same ground in 15 seconds. “They put us through the wringer for two years,” he said. “We want to make sure that these measurements are really sub-millimeter, that you’re really right in saying where they are. So they take parts, measure it with their system, our system, then they put it on a CMM. We got it commercially viable and then launched in the States through our group NorthStar Vision, and now we're adding more features.”

The key to efficiency and cost control for the suppliers and manufacturers, one Skillreal adviser said, is to detect the problem before the next part is built or sub-assembly completed.

The SkillReal software can support up to eight cameras from the same PC running an NVIDIA graphics processing unit. Workers can be trained to use the system in a single eight-hour shift, Grabowski said.

SkillReal’s founder and CEO is Shai Newman. Before Skillreal, Newman founded Compedia, a company that helps publishers transform their content into virtual 3D educational environments. The idea for the 2D-camera inspection technology was born when Siemens approached Compedia in its own search for a system that it hoped would power some kind of augmented reality glasses for the manual line inspectors.

Asked to detail the inner workings of the math, Grabowski said the algorithm does “billions of hardcore computer-vision calculations” that actually break the 2D image up pixel by pixel. “It does the same thing with a 3D model for that perfect overlay,” he said. “And then we layer the AI on top so we can know where to look.” In a nifty compute-saving trick, the system only scans where the components are supposed to be. In other words, there’s no need to waste processor power analyzing locations that don’t include features to inspect.

Grabowski said the company does see more future uses of the technology. “The automotive body in white is our bread and butter for the time being,” he said. “But we see expansion into final assembly of automotive interior trim panels and more. There are so many different avenues that we can use this in automotive alone. No one's doing this type of ultra-fast, sub-millimeter accurate dimensional check.”

He said the company believes its first-mover advantage and series of patents protect it against potential competitors.

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