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How spatial computing makes it easier to train new talent, stay compliant, and detect defects

When Apple teased its Vision Pro headset last year, it also teased out the term: “spatial computing.” The Vision Pro itself became available this year, and we’ve been experimenting to see what all the fuss is about—and to try to understand what spatial computing might be able to achieve in various contexts.

Our initial take: this is the real deal. And while much of Apple’s marketing has focused on consumer uses, the most exciting potential we see is for enterprise applications. Here’s a look at three use cases we’ve uncovered for industrial organizations, where the Vision Pro’s high resolution, collaboration capabilities, and unique functionality could lead to game-changing applications.

1. How spatial computing can make training safer

Mobile apps have enabled industrial organizations to make on-the-job training and education much easier and more accessible: with training apps, workers can complete modules in short segments during their down time. They can quickly look up safety information. They can get reminders to update a certification before it lapses.

Spatial computing unlocks a whole new world of training. Thanks to the Vision Pro’s ability to create high-definition hybrid worlds, it’s now possible to teach workers how to use heavy machinery without any of the risks of operating real-world models.

Here’s how: the Vision Pro lets you create realistic 3D projections (how realistic? In one demo, everyone kept ducking to get into the cab of a nonexistent vehicle we were projecting onto empty floor space).

The training implications are significant: rather than having workers study a book or even watch videos, you can have them operate virtual equipment to experience firsthand why, say, overloading a forklift is dangerous or what happens if they don’t secure a robotic arm properly after servicing it.

The experience is just like doing the actual work—minus the risk.

For industrial companies, this means employees can do more sooner, learn the job faster, and operate more safely at all times.

And think of the potential for distance training: you could have one trainer at headquarters guiding workers at multiple facilities through use of equipment, with virtually no risk of bodily injury or property damage.

Related: Industrial organizations: scale operations to enhance employee productivity and reduce burnout

2. How spatial computing can make compliance easier

Quality assurance and quality control are essential parts of maintaining compliance. Spatial computing can make that work more efficient and even more intuitive by offering a more experiential way of doing root cause / failure analysis (RCFA) when something goes wrong.

RCFA, of course, involves gathering complex data about failures and analyzing it to pinpoint a root cause. One of the most compelling early applications for spatial computing is its ability to facilitate data analysis.

Because spatial computing makes it possible to view data in three dimensions, the process of “analysis” becomes more a process of “experience.” QA and QC professionals can create graphs with a x, y, and z axes, rotate them to consider data from various angles, and see relationships that might remain invisible in a two-dimensional chart.

What's more, the “infinite screen” that spatial computing allows means that QA and QC professionals can view as many data sources as they want simultaneously, again facilitating the work of uncovering relationships, trends, and patterns—and, ultimately, finding answers.

Getting to those answers faster means manufacturers and logistics companies can scrap less work, do less rework, and slash downtime.

Another, simpler application: instead of having quality control associates painstakingly type out SOP documents, a spatial computing headset could simply record their activities as they carry out the process in question, translate their actions using an AI motion-to-text application, and output an SOP doc for the associate to edit. Scaled across an organization, the time savings would be significant.

As spatial computing headsets became ubiquitous, the SOP doc might die out completely in favor of a 3D recording other associates could follow.

3. How spatial computing can detect defects better

Automating defect detection has been a challenge for many industries and for certain complex inspection tasks within industries—verifying weld seams on auto frames, for example, or checking the integrity of bottle labels.

Spatial computing could provide a solution.

One hypothetical example: A human inspector wearing a Vision Pro headset could essentially turbo-charge their ability to detect defects, using the headset as backup for distraction, fatigue, and other sources of human error. At the same time, an app in the headset can record countless images of acceptable and defective parts—in different lighting conditions, different orientations, from different angles, with different backgrounds, etc.

This data could then be used to train an AI model to make machine-only detection ever more accurate.

After the fact, analysts equipped with Vision Pros can look at defect data in three dimensions, so that they can more easily identify trends and patterns that lead them to solutions.

The future is getting bolder and brighter for manufacturing and logistics companies

As exciting as the applications we discuss in this article are, they represent only the very beginning of our understanding of what's possible with spatial computing. Think of it this way: the iPhone launched in 2007. The first version of Uber didn’t launch until 2009.

In other words, we’re in the earliest days of understanding the scope of what's possible with spatial computing in the industrial space. As forward-thinking organizations experiment and learn, the gap between leaders and laggards will grow significantly.

The best way to prepare your organization to be among the former? Make sure your data is in order. The potential applications of spatial computing are significant, but they all require underlying data maturity.

Not sure where your data stands? Check out our Data Maturity Accelerator, a one-week engagement that delivers you a roadmap to getting your data where it needs to be to take advantage of all Industry 4.0 has to offer.

Published by Ed LaFoy , Benedict Wong , Harold Sawal in Spatial Computing

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