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Extended reality (XR) can put machine status, instructions and robot workflows into a worker’s view, or let teams practise and collaborate in virtual factory spaces. Early studies report benefits for specific tasks such as alarm response, preventive refills and collaborative-robot programming, but they do not establish a universal productivity gain or payback period. Comfort, field of view, tracking, safety and integration with factory systems determine whether a promising demonstration can work on a production floor.
What “open XR” means on a factory floor
XR is an umbrella term for augmented reality (AR), mixed reality (MR) and virtual reality (VR). In industrial settings, these interfaces connect a person to spatially relevant machine information or workflows. AR and MR can show information in a view of the physical workplace; VR replaces that view with a simulated environment.
“Open XR” should not be taken to mean that every industrial headset or factory system already works together through one open standard. The evidence here concerns industrial XR broadly. OpenXR-related frameworks appear in the European Commission’s XR5.0 work on interoperability, but that project is developing approaches rather than demonstrating universal compatibility. XR5.0 also emphasizes worker well-being, privacy, security and data sovereignty as part of human-centric Industry 5.0.
The practical idea is to connect a worker’s location and task with machine-performance data, then present information in context. NIST described this approach in Industrial XR: Fulfilling Human Potential in Smart Factories (2020). For example, instead of looking up an alarm code on a separate screen, a worker might see the alarm or a maintenance instruction associated with the equipment that needs attention.
Which XR mode fits which factory task?
| Mode | What the worker experiences | Factory tasks supported in the cited evidence | Main consideration |
|---|---|---|---|
| AR | Digital information is layered over a view of the real workplace, often through a head-mounted display. | Assembly guidance, inspection, remote troubleshooting and machine-status displays. | Workers must still see and move safely in the physical environment; visibility, tracking and comfort matter. |
| MR | Digital content is presented in relation to the physical space, with the interface intended to support interaction with real equipment. | Real-time process control and experimental interfaces for programming collaborative robots. | Spatial alignment and interaction must be reliable, and the interface should not add physical strain or confusion. |
| VR | The user enters a simulated environment rather than viewing the real factory through the headset. | Simulation, training and remote collaboration or planning in virtual factory spaces. | It is better suited to rehearsal or virtual collaboration than to tasks that require direct sight of operating equipment. |
These are useful distinctions, not rigid product categories: an industrial workflow may combine modes or pair a headset with a conventional screen. The right choice follows from the task. A worker responding to a live equipment alarm needs a different interface from a team rehearsing a layout or safety scenario.
Where XR is being used with industrial machines and robots
Process monitoring and alarm response
A 2025 learning-factory study by Amouzgar and Willebrand compared a Microsoft HoloLens 2 XR system for real-time process control with a conventional two-dimensional human-machine interface (HMI). The analysis covered 22 participants. The authors reported faster alarm response, more frequent preventive refills and higher usability with XR than with the 2D HMI. They also identified ergonomic and field-of-view limitations. These results concern the studied system and tasks; they are not proof that an XR display will improve every factory process.
Collaborative-robot programming
Programming a collaborative robot (cobot) can involve teaching positions and tasks through a pendant or another interface. NIST’s 2024 preliminary study evaluates AR and VR interfaces for programming a cobot on a standardized assembly task board. Its motivation includes reducing physical strain and operator confusion associated with current approaches. This is an evaluation of interfaces, not evidence that mixed reality has already replaced teach pendants in production.
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Inspection and remote troubleshooting
A 2024 Australian heavy-manufacturing case described AR head-mounted-display use for electrical assembly, cobot inspection and video-call troubleshooting. Howard and colleagues reported a mean System Usability Scale (SUS) score of 69.8 for the AR headset alone and 79.2 for the integrated work system, alongside a mean NASA Task Load Index (NASA-TLX) score of 25.8. These measurements describe one case, not a universal benchmark for headset usability or workload.
Factory planning, training and remote collaboration
In a 2024 automotive innovation-center case, Hakanen and colleagues combined an autonomous mobile robot (AMR) digital shadow or point cloud with an XR platform. The setup supported visualization, audio and multi-user interaction in a virtual factory. The qualitative case involved 36 participants and identified factory-cell and work planning, remote technical support and safety training as potential applications. Those are proposed uses emerging from a case study, not quantified production outcomes.
What the evidence says—and what it does not
The strongest evidence in these examples is task-specific: one learning-factory comparison found better alarm response, preventive-refill behavior and usability; a manufacturing case reported usability and workload measures; and preliminary or qualitative work explored cobot programming and virtual-factory collaboration. Each result depends on the task, device, software, worker training and factory integration.
HTC VIVE’s 2024 survey of 400 U.S. manufacturing professionals reported that 50% were currently using XR. Among respondents not using it, 59% said they intended to adopt XR within five years and 74% within ten years. These are vendor-survey adoption figures, not independent measurements of productivity, successful deployment or return on investment.
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The available examples do not establish a neutral, cross-industry productivity statistic, a universal payback period, or a standardized safety-certification path for every XR-and-robot configuration. A pilot should therefore define its own measurable outcome—such as time to respond to a particular alarm, completion accuracy, training performance or troubleshooting time—and compare it with the existing workflow.
What can make a factory XR pilot succeed or fail?
Fit the interface to the task
Use spatial overlays when information needs to be associated with equipment or a work location. Consider VR when the goal is simulation, rehearsal or collaboration in a virtual representation of the factory. For robot programming, compare the XR interface with the current pendant or control method on a representative task rather than assuming a more immersive interface will be easier.
Test ergonomics and visibility in real conditions
Headset comfort, physical strain, field of view, tracking and gesture quality affect whether a worker can use the system while doing the job. A lab or demonstration setup may not reflect long shifts, varied lighting, protective equipment, movement or interruptions. The HoloLens 2 study’s reported ergonomic and field-of-view limitations are a reminder to test those constraints rather than treating the display as an incidental choice.
Integrate with operational systems and safety practices
Machine data has to reach the XR interface accurately and at the right time. A deployment may need connections to manufacturing execution systems (MES), robot-control systems or other factory data sources. Teams also need to consider cybersecurity, access control, privacy and who governs the resulting operational and worker data. XR should not obscure hazards, replace required safety procedures or invite a worker to interact with a robot in an unsafe state.
Plan for interoperability and worker acceptance
Headsets, applications, robot systems and factory data platforms do not become interoperable simply because they use XR. Verify the specific devices, software interfaces and data flows involved. Train workers, collect feedback on confusion or burden, and make sure the system has a safe fallback if tracking or connectivity fails. The European Commission’s XR5.0 project places interoperability alongside well-being, privacy, security and data sovereignty because these concerns shape whether human-centric XR can scale.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical way to evaluate a factory XR use case
- Choose one bounded workflow. Start with a defined task such as responding to a recurring alarm, inspecting a particular assembly or rehearsing a safety procedure.
- Record the current baseline. Measure the existing workflow with the same outcome you will use to judge XR, such as response time, task accuracy or troubleshooting duration.
- Select the interaction mode. Decide whether workers need overlays in the physical environment, an MR interface for equipment interaction, a VR simulation, or a combination.
- Test the complete workflow. Include real equipment or a representative setup, the intended headset and software, factory data connections, worker training and normal safety controls.
- Evaluate burden as well as benefit. Check task performance alongside comfort, field of view, tracking reliability, workload, usability and worker feedback.
- Set a scale-up threshold. Expand only if the pilot improves a defined operational outcome without creating unacceptable safety, ergonomic, privacy or integration problems.
Is the industrial metaverse practical yet?
Some pieces are practical in bounded settings: contextual machine displays, remote assistance, robot-programming experiments and virtual factory collaboration have all been studied or demonstrated. The automotive AMR case shows how a digital shadow can support shared visualization and interaction, while the learning-factory study provides a comparison with a conventional HMI. Neither establishes that a fully connected industrial metaverse is a standard, broadly deployed factory solution.
For manufacturers, the useful question is not whether to adopt a metaverse label. It is whether a specific XR workflow solves a real operational problem better than the existing interface, and whether it remains safe, usable and supportable when connected to the actual factory.
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