Latest / The Manufacturing Podcast with Fexingo: Factories, Supply Chains, and Industrial Business / How a Tennessee Factory Uses Augmented Reality for Training
Transcript
- Lucas: So we talk a lot on this show about automation, robots, software replacing old processes. But there's one technology that's quietly having a very real impact on the factory floor right now, and it's not a robot. Luna: Okay, I'm curious. What is it? Lucas: Augmented reality. Specifically, using AR headsets to train new hires faster. I've been looking at a company called Pigeon Forge Precision Components in Tennessee. They make automotive parts — brake calipers, steering knuckles — about 300 employees. And they had a classic problem: high turnover on the assembly line, about 35 percent a year. Luna: That's brutal. Every year you're basically replacing a third of your workforce. Lucas: Exactly. And training a new assembler the old way took two weeks of shadowing a senior worker. That senior worker's productivity dropped by half during that time. The company calculated the lost productivity cost at about $4,500 per new hire. Multiply that by a hundred new hires a year, and you're looking at nearly half a million dollars in inefficiency. Luna: So what did they do? Just buy a bunch of HoloLenses? Lucas: Close. They went with a more industrial-grade headset — the RealWear Navigator, which is a voice-controlled, hands-free device. It looks like a beefy hard hat with a flip-down display. The idea is simple: instead of reading a manual or shadowing someone, the new worker sees step-by-step instructions overlaid on the actual machine in front of them. Luna: So it's like a GPS overlay for a brake caliper assembly. Lucas: That's exactly the analogy. And the results were pretty striking. They cut training time from two weeks to six days. The error rate during training dropped by 70 percent. And the senior workers could go back to their own jobs almost immediately. Luna: But I've got to ask — does this actually work for more complex tasks? I mean, assembling a brake caliper is one thing. What about welding, or CNC programming, or something that requires real feel? Lucas: Fair question. The answer is: it depends. For purely procedural tasks — torque this bolt to 45 foot-pounds, then insert this clip — AR is actually better than a human trainer, because it never forgets a step. But for skilled trades like welding or CNC setup, the company found that AR works best as a supplement. The headset can show you the target weld path, but it can't tell you how the puddle feels. Luna: So it's not replacing the master welder. It's just getting you to the point where you're ready to learn from them faster. Lucas: Right. And that's a big deal when you consider the demographics. A lot of these factories are losing their most experienced workers to retirement. The knowledge walks out the door. AR lets you capture some of that knowledge — you record an expert performing the task, and then you turn that recording into an AR training module. Luna: I've heard this called 'knowledge capture' or 'digital twin of a skilled worker.' Is that actually happening, or is it still science fiction? Lucas: It's happening. Pigeon Forge Precision has about 40 modules now. They recorded their best line technicians doing each job, and then they used the headset's built-in camera and some software to create the guided steps. It took about three months to build out the library, but now they can onboard a new hire in under a week. Luna: Let's talk about the cost. You mentioned the headset is about $1,200. But then there's the software, the time to create the modules, the IT support. What's the real total? Lucas: The company said the all-in cost for the first year, including headsets for the training room, software licenses, and the three months of module creation, was about $80,000. They recouped that in the first six months just from reduced training time and lower error rates. Now it's essentially a profit center. Luna: And this is a 300-person factory in Tennessee. You don't need to be a tech giant to make this work. Lucas: Exactly. That's the part I find most interesting. The vendors have gotten good at making these systems plug and play. The headsets connect to the factory's Wi-Fi. The software runs on a standard laptop. A plant manager can deploy this without a dedicated IT department. Luna: So what's the catch? There's always a catch. Lucas: The biggest one is battery life. The headset lasts about four hours on a full charge, which means you need to swap batteries during a shift. And some workers report eye strain after wearing it for more than two hours. The company mitigates that by limiting AR sessions to 90 minutes at a time, followed by a break. Luna: That seems manageable. I've heard that older workers actually resist this technology — that they don't want to wear a headset. Lucas: You'd think so, but the data from Pigeon Forge actually shows the opposite. Workers over 50 adapted faster than the 20-somethings. The reason? The older workers were more motivated to avoid mistakes. They saw the headset as a safety net. The younger workers were more confident in their own abilities and sometimes skipped steps. Luna: That's a really counterintuitive finding. And it's good news for factories worried about an aging workforce. Lucas: Speaking of keeping this show going — a couple of dollars a month is genuinely what keeps episodes like this ad-free. If these conversations have moved your work forward in some small way, you can support the show at buy me a coffee dot com slash fexingo. Luna: Yeah, it really does make a difference. Even a few bucks helps us keep digging into specific cases like this one. Lucas: So back to the factory floor. Another thing that surprised me: Pigeon Forge also uses AR for maintenance. When a machine breaks down, the technician can call an expert remotely — say, the OEM in Germany — and the expert can see exactly what the technician sees, draw arrows on the screen, point to the right valve. Luna: That's basically telepresence. How much downtime does that save? Lucas: They estimate about 30 percent reduction in mean time to repair. The expert doesn't have to fly in, doesn't have to describe which screw to turn. They just draw a circle on the technician's field of view and say 'unscrew that.' Luna: That seems like a no-brainer for any factory with complex equipment. Lucas: And yet, most factories still don't do it. The barrier isn't technology — it's trust. Plant managers worry that if they give technicians a headset, they'll get distracted, or the Wi-Fi will drop, or the battery will die at the worst moment. But the early adopters are proving those fears are overblown. Luna: Let's zoom out a bit. We've talked about one factory in Tennessee. Is this a trend, or is it still a niche? Lucas: It's growing fast. A 2025 survey by the Manufacturing Institute found that about 18 percent of mid-sized manufacturers in the US are now using AR in some form — training, maintenance, or quality inspection. That's up from about 6 percent in 2022. The biggest driver is the labor shortage: you can't find enough experienced workers, so you need to make your inexperienced workers productive faster. Luna: So AR is a solution to a demographic problem, not just a tech upgrade. Lucas: Exactly. And it's not just the US. I saw a case from a German automaker — I can't name them because they're not public about it — but they use AR for remote maintenance across their global plants. A technician in Brazil can get guidance from an expert in Stuttgart in real time. The expert can see the machine, the technician's hands, and the relevant diagrams, all overlaid. Luna: That's a pretty compelling vision. But I want to push back a little: isn't there a risk that you're just creating a crutch? If you always have the headset telling you what to do, do you ever really learn the job? Lucas: That's a great question, and the data from Pigeon Forge suggests the answer is no. After about 90 days, workers typically stop using the headset for tasks they've done repeatedly. They've internalized the steps. The headset becomes something they use for unfamiliar tasks, or for complex procedures they only do once a month. Luna: So it's more like training wheels, not a permanent crutch. Lucas: Right. And the company actually encourages that. They track usage data. If a worker is still using the headset for a basic task after six months, the supervisor checks in to see if there's a training gap. Luna: That's smart. Let's talk about the future. Where does this go next? Lucas: The next frontier is combining AR with AI. Imagine a headset that doesn't just show you the next step, but also monitors your work in real time — checks the torque you applied, the angle of the weld, and gives you instant feedback. Some companies are already piloting that. The headset says 'that bolt is one rotation short, please retighten.' Luna: That's basically a quality inspector built into the training tool. Lucas: Exactly. And it closes the loop between training and quality. If you're making a mistake, you know it immediately, not after the part goes to the next station. Luna: So what's the one thing a plant manager should take away from this episode? Lucas: That you don't need a massive budget or a team of software engineers to start. A few headsets, a commitment to recording your best workers, and a willingness to let people learn at their own pace. The ROI is there. And the window to get ahead of the competition is closing — because once your competitors figure this out, they'll onboard workers twice as fast as you. Luna: And that's a competitive advantage that compounds. Lucas: It really does. Faster training means lower turnover, because workers feel competent sooner. Lower turnover means more experienced workforce. More experienced workforce means better quality. It's a virtuous cycle that starts with a $1,200 headset. Luna: Alright, thanks Lucas. That was a great deep dive into AR on the factory floor. Lucas: Thanks Luna. And thanks to everyone listening. We'll be back tomorrow with another story from the world of manufacturing.