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AR flopped with manufacturers. Here’s why spatial computing is different

When augmented reality (AR) headsets from major tech companies became available a few years ago, there was a great flurry of activity around finding applications, particularly in the manufacturing space.

A few years on, however, AR hasn’t caught on in most industrial environments. Still, when Apple launched its Vision Pro earlier this year, touting new “spatial computing” capabilities, we decided to test the device out for ourselves. Our take: this isn’t just AR with a facelift.

In fact, spatial computing can have profound impacts on manufacturing operations. Here’s a look at why—and what makes it so different from the AR of a few years back.

AR in manufacturing: A solution in search of a problem

AR headsets make it possible to project digital information onto the real world—hence the name “augmented reality.” In theory, the applications for manufacturing seemed endless: workers on the floor could project assembly instructions onto parts in front of them, for example, or turbo-charge their ability to spot defects on a QA line.

In reality, though, those applications fell flat for several reasons:

  1. AR headsets can be cumbersome. For workers whose job is already physical, adding additional weight can increase strain on the body and make injuries more likely.

  2. In some cases, the headset design interfered with necessary personal protective equipment (goggles, helmets, etc.).

  3. To function properly, AR headsets demand high-speed wireless internet with very low latency. Many factory floors were not adequately equipped, meaning digital information couldn’t load fast enough to be helpful.

  4. Temperatures in manufacturing facilities can vary widely—from sub-freezing to steamy hot. These are not ideal conditions for operating AR headsets.

  5. Many AR applications rely on auditory or gesture commands, but manufacturing facilities can be noisy. What's more, workers may be wearing PPE that obscures their faces or hands. Both can interfere with how the AR headset functions.

  6. Finally, AR is a net-new technology for the majority of workers. Adopting new tech is difficult at the best of times; when a device already has so many strikes against it, getting workers to adopt it can be impossible.

So while the theory of AR in manufacturing was compelling, its reality was disappointing.

Spatial computing is fundamentally different.

What's different about spatial computing

If the main (theoretical) function of AR in manufacturing was to overlay digital displays on a physical reality, the main function of spatial computing (as of right now) is to experience data in three dimensions.

As you can imagine, that changes the conversation about how and where to apply this technology in a manufacturing setting: rather than focusing on the factory floor, we’re now looking at what's possible for workers who currently spend a lot of time in labs, offices, or any location that requires significant data analysis.

For example: imagine a new composite material made from plastic trash removed from waterways. You’re a manufacturer trying to determine whether you might be able to swap out existing material inputs for this replacement—and address some of your Scope 3 emissions in the process.

Rather than poring over specs on endless two-dimensional graphs and charts, spatial computing would let you experience those specs—hardness, elasticity, melting point, etc.—in three dimensions, so you might more easily compare them with established parameters.

You could more quickly determine whether the material is a viable alternative, and more easily calculate what other specs might need to change to accommodate it.

3 spatial computing applications that will change manufacturing

For now, Apple’s Vision Pro doesn’t fully solve the problems that AR headsets had for workers on the factory floor. It’s heavier than Meta’s Oculus and Microsoft’s Hololens, for one thing—the single biggest drawback of the device at this point (and something we expect to get better in future models).

But its enhanced capabilities in other realms—higher-resolution digital displays and an experience less likely to cause nausea among them—mean it’s a device to take seriously in the manufacturing industry as a whole.

Among the immediately viable applications we’re most excited about:

  1. Safer training environments. Because of the Vision Pro’s extremely high-definition display, virtual environments it creates feel real. As we’ve mentioned elsewhere, this has huge implications for training workers to do dangerous tasks or work in dangerous environments.

  2. Faster root cause / failure analysis. RCFA is complex, data-intensive work. Spatial computing makes it possible to consider data in three dimensions, making it easier to make connections, see associations, and complete RCFA.

  3. Easier supply chain management. Supply chains are among the most complex systems in all of manufacturing. By making it possible to interact with supply chain data in three dimensions, spatial computing makes the work of supply chain management more tangible and therefore facilitates decision-making. The difference between two-dimensional and three-dimensional data representations is akin to the difference between looking at a spreadsheet of numbers and looking at a visualization of those numbers—an enormous impact on comprehensibility.

  4. Remote collaboration. In addition to presenting data in three dimensions, spatial computing makes it possible for multiple people to interact with the same 3D dataset while in different physical locations. The implications for supply chain management or RCFA, for instance, are immediately obvious. Spatial computing makes it possible to collaborate in real time on your toughest challenges, no matter where your best minds are located.

Spatial computing will catapult Industry 4.0 forward

Already, savvy deployment of Industry 4.0 technologies is defining the manufacturing leaders of tomorrow and helping them pull away from last century’s titans. Spatial computing is yet another capability that will let innovative manufacturing organizations sail ahead of the competition.

Whether you’re feeling ready to experiment with this newest technology or wondering how you can catch up, we’d love to talk.

If Industry 4.0 is new to you, the first step is often getting your data in order. In just a week, we can put together an assessment of your current data maturity and provide you with a roadmap of how to get to a point where you can use tech like spatial computing, internet of things (IoT), smart sensors, machine learning, and more to transform your organization.

Published by Ed LaFoy , Patrick Turley in Spatial Computing

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