The Challenge
CASFER is building a future where fertilizer production is cleaner, more local, and less dependent on fossil-fuel-based supply chains. That future depends on real systems, operated safely and consistently, across a distributed network of universities, labs, and industry partners.
CASFER’s fertilizer conversion unit turns agricultural waste into nutrient-rich fertilizer. It is real hardware doing real work, but it is also complex equipment that requires precise operation, monitoring, and troubleshooting.
In environments like this, manuals are necessary, but they do not create readiness. Reading instructions and watching a task performed is not the same as building the familiarity needed to operate a system confidently under real conditions.
The challenge is not a lack of documentation or expertise. It is the gap between understanding a system in theory and being able to execute in practice, consistently, across people and locations. CASFER needed a way to make complex processes visual, teachable, and repeatable before someone ever steps on site.
AVATAR’s Solution
AVATAR partnered with CASFER to build a true digital twin of the fertilizer conversion unit using XRcreate. The goal was to create a spatially accurate, interactive representation of the system that supports hands-on learning, not passive observation.
With XRcreate, CASFER’s system becomes something users can explore, interact with, and practice. Instead of relying on one-time demonstrations, users can rehearse operational steps, learn the machine’s layout and logic, and develop the confidence that comes from repetition.
This approach shifts training from “watch one, do one” to “practice before you perform.” In a headset, users are not just looking at a model. They are learning by doing, building the kind of muscle memory that reduces hesitation and improves execution when working with the real system.
Because the experience is managed inside XRcreate, training content can be updated centrally and delivered across devices. This supports CASFER’s distributed model, where the same system knowledge must be taught and retained across multiple institutions and partners.
In short, the digital twin becomes a training environment that makes complex sustainability technology understandable, teachable, and scalable.
Impact / Outcome
CASFER can train and onboard users in a way that matches the real demands of operating advanced equipment. Users build familiarity before they ever touch the hardware. Decisions and motions feel less foreign. Troubleshooting becomes faster and safer because the system is already mentally mapped through repeated interaction.
This also supports CASFER’s broader mission. When complex processes become easier to visualize and rehearse, training becomes more consistent across the network. Institutional knowledge is preserved in a form people can actually use. And the technology transfer path becomes stronger, because the system can be demonstrated and understood without requiring physical access or risky conditions.
The outcome is practical readiness in support of national-scale sustainability goals: better-prepared operators, safer field work, and training that keeps pace with innovation rather than lagging behind it.
Ready to make complex systems trainable before the moment of execution? We are. If you’d like to learn more or talk through what this could look like for your program, click here to connect with our team.
