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hough we spend ample time examining consumer-based AR endpoints, greater near-term impact is seen today in the enterprise. This takes many forms including camera commerce and collaboration. But the greatest area of enterprise AR impact today is in industrial settings.

This includes AR visualization to support assembly and maintenance. The idea is that AR’s line-of-sight orientation can guide front-line workers. Compared to the “mental mapping” they must do with 2D instructions, line-of-sight support makes them more effective.

This effectiveness results from AR-guided speed, accuracy, and safety. These micro efficiencies add up to worthwhile bottom-line impact when deployed at scale. Macro benefits include lessening job strain and the “skills gap,” which can preserve institutional knowledge.

But how is this materializing today and who’s realizing the above enterprise AR benefits? Our research arm ARtillery Intelligence tackled these questions in its report: Enterprise AR: Best Practices & Case Studies, which we’ve excerpted below, featuring Boeing and Upskill.

Enterprise AR: Best Practices & Case Studies, Volume One

High Stakes

One of the themes seen throughout this report is that AR can have outsized value when the stakes are high. In other words, AR’s ability to make work faster and/or more accurate is especially valued when the products being assembled are “high-ticket” items.

As examined in our GE case study, nowhere are these stakes higher than in the world of aerospace. This is the case for leading commercial aircraft manufacturer Boeing, which has dizzying levels of complexity in the construction of each plane – everything from engines to wiring.

In fact, 130 miles of wiring go into every new aircraft. And laying that wire requires high degrees of precision, and little margin for error. Things get even more complex when you consider that each Boeing aircraft – from the 737 to the 787 – has unique wiring configurations.

This adds up to tens of thousands of hours of work each year. And the traditional method for guiding wire placement involved paper manuals packed with diagrams. Technicians would repeatedly shift attention to check these diagrams and schematics.

To reduce that cognitive load – a leading cause of mistakes – Boeing implemented Google Glass with Upskill Skylight. By eschewing the cross-checking method in favor of line-of-sight instructions for its wire harnesses, the goal was to speed up and improve assembly.

Case Study: GE Streamlines Jet Engine Maintenence

Cognitive Load

Going deeper on Boeing’s AR deployment, it let technicians move through multiple instruction prompts using voice commands, Google Glass gestural taps and a head-tracking interface. Voice commands could also summon a particular sequence of schematic instructions.

This voice-based approach is particularly additive to wire assembly, given that it’s a process that requires maximum dexterity and freedom of movement with all ten fingers. Additionally, bar code readers and Google Glass cameras helped technicians identify specific wires.

Beyond these automated line-of-sight features, technicians have the option to call in a remote expert for “see what I see” support, given Google Glass’s built-in camera and voice input. Technicians can also stream how-to videos directly in their field of view without looking away.

And the result of these AR implementations? Boeing was able to reduce error rates to zero. It also cut its wiring production time by 25 percent. The former is important when talking about passenger jets given the importance of safety. And the latter breeds bottom-line savings.

“Rather than picking up seconds or minutes, a step function change gives us an opportunity to cut the build time by 25 percent,” Boeing Senior Manager Randall MacPherson told Upskill. “Wearable technology is helping us amplify the power of our workforce.”

We’ll pause there and circle back in the next report excerpt with another case study…

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