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Extended reality (XR)—virtual reality (VR), augmented reality (AR) and mixed reality (MR)—can give industrial workers a place to practise a task before performing it on real equipment. Current examples include VR assembly and factory-layout exercises, and an XR interface for responding to machine alarms. Those examples show how XR can support training; they do not establish that it generally prevents injuries, improves long-term retention or cuts total training costs.
How is XR used for factory training?
XR is an umbrella term, not a single training format. VR places a learner inside a simulated environment; AR and MR can add digital information to a view of the physical workspace. The choice depends on what the worker needs to learn: practise a sequence away from the line, understand a layout, or interact with information related to a machine.
A virtual environment can make it possible to repeat a task without staging the same physical setup each time. That is potentially useful when a task is complex, costly or hazardous to rehearse on operating equipment. Whether the simulation teaches the right skill depends on its accuracy, the quality of instruction and how the learner is assessed.
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VR practice in a learning factory
A 2025 descriptive study in Computers & Education: X Reality evaluated a VR environment based on the LEAD Factory at Graz University of Technology. Thirty participants worked on assembly and layout-planning tasks, including designing a custom workflow. In that study, 67% produced high-quality functional designs. Participants also reported a mean System Usability Scale score of 83.9, mean interest of 5.9 out of 7, and mean NASA-TLX cognitive-load score of 4.44 out of 20.
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These results describe performance and participant responses in that particular learning-factory task. They do not, on their own, show that VR outperforms another training method, that skills transfer to a production floor, or that workers retain those skills over time.
XR interaction with machine information
A 2025 paper in the Journal of Manufacturing Systems describes an XR real-time machine-interaction system evaluated in a learning factory using Microsoft HoloLens 2. Its abstract reports improved usability and shorter alarm-response time compared with 2D human-machine interfaces (HMIs). The result is specific to that evaluation; the reported abstract does not provide enough detail to assume the same effect in another factory, with different equipment or under different operating conditions.
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Provider-reported deployment
Industrial XR provider IndustryVR says its simulator can be deployed on a single Meta Quest 3. That is a statement about the provider’s offering, not evidence that one headset is sufficient or suitable for every site. Device fit, software compatibility, support and the realities of the work environment still need to be checked with the provider and tested locally.
What do manufacturer surveys say about adoption and safety?
HTC VIVE’s 2024 survey of 400 U.S. manufacturing professionals offers a snapshot of respondents’ reported XR use, not a representative census of all manufacturers. HTC VIVE reported that 50% of respondents already used XR. In the same survey, 70% of manufacturers already using XR had implemented it in training.
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HTC VIVE also reported that 95% of industrial professionals using XR felt safer on the job after learning in an XR-simulated environment. This is a reported perception, not a measured reduction in incidents or injuries. The survey report page further says that, at the time of the survey, 59% of manufacturers not yet using XR intended to start within five years and 74% within a decade. These are stated intentions from 2024, not forecasts or current adoption figures.
Which training approach fits the task?
VR practice, in-situ AR/MR guidance and conventional instruction solve different problems. The following comparison is a buyer’s framework, not a head-to-head trial result; the available studies describe particular VR and XR learning-factory evaluations rather than comparative economics across factories.
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| Approach | Best-fit question | What to evaluate |
|---|---|---|
| VR learning module | Can the worker practise a sequence, assembly task or layout decision in a simulated environment before doing it physically? | Whether task steps and virtual assets match current work instructions; how performance is scored; whether practice transfers to supervised work. |
| AR/MR machine guidance | Does the worker need digital information or interaction while looking at or working near physical equipment? | Visibility, comfort, device suitability in actual work conditions, integration with machine information and response performance. |
| Instructor-led and hands-on training | Does the worker need physical practice, human feedback, or a sign-off on real equipment? | Instructor oversight, access to equipment, consistency of assessment and how practical competence is verified. |
XR can be considered as a supplement to established instruction rather than assumed to replace it. For safety-critical tasks, define what a learner must demonstrate on actual equipment and who is responsible for approving competence.
How should a factory evaluate an XR training pilot?
Start with a defined task and an outcome that matters operationally. A pilot should test not just whether a module is engaging, but whether workers can perform the target task to the required standard.
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- Choose the task or failure mode. Specify what workers must learn and why existing instruction needs an additional practice format.
- Set a competence measure. Decide whether success means procedure accuracy, response time, retention after a delay, or supervised performance on real equipment. Record a baseline or comparison where feasible.
- Check instructional and equipment fidelity. Have subject-matter experts verify that the virtual assets, machine behavior and procedures match current equipment and approved work instructions.
- Confirm the device and operating fit. Check hardware and software compatibility, hygiene, comfort, visibility, fleet administration and performance under workplace conditions. Confirm integration and update responsibilities.
- Set oversight and sign-off rules. Identify what instructors review, when a worker moves to hands-on practice, and who approves readiness for safety-critical work.
- Define the expansion decision in advance. Track the agreed performance measures and the setup, integration and content-update effort. Decide what evidence would justify expanding the pilot, revising it or stopping it.
There is no established head-to-head economic comparison in the cited examples that demonstrates XR is cheaper than conventional industrial training. A local pilot should account for the whole training system, not just headset cost.
What are the limits of XR training evidence?
- The 30-person VR learning-factory study is descriptive and task-specific; its usability, interest and design results are not proof of long-term learning transfer.
- The machine-interaction finding comes from a particular learning-factory evaluation and does not establish effects across other factories or operational settings.
- The HTC VIVE safety result is self-reported perception, not an injury-rate analysis. Its adoption and intention figures describe survey respondents at the time of a 2024 U.S. survey.
- Provider claims about deployment, customer outcomes or standards alignment should not be treated as independently verified evidence without corroboration.
XR is best treated as a training and operational tool to evaluate against a specific task, with human instruction and real-world competence checks where needed—not as a guaranteed safety or cost solution.
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