Most product teams have the same problem with prototyping. Making a physical model costs too much time. It costs too much money. And even after all that effort, you discover the design is wrong, and you must do it again. This creates a difficult loop that limits how much engineers can actually iterate and learn. A team of researchers from the University of Bristol looked carefully at this problem. Their answer is simple but clever: use Lego bricks and 3D printing at the same time, inside the same prototype. Their study, published in the journal Design Science, shows this "hybrid" approach can reduce fabrication time by up to 56% and cut material waste by up to 76%.
When you build a prototype, you usually pick one method and stick to it. You either 3D print everything, or you build everything from Lego. Both approaches have their own strengths, but they also have clear limitations.
So, the idea of hybrid prototyping is this: what if you use each method where it is strongest? You use Lego for the internal structure and the parts that do not need high visual quality. You use 3D printing only for the surfaces that matter — like button layouts, grip surfaces, or areas that users will touch. This is not a new idea completely, but until now there was no systematic study of how to do it, which approach gives the most benefit, and under what conditions.
The authors propose three distinct strategies. Each one addresses a different design goal. In practice, you can combine them too.
The first approach is about choosing where fidelity is important. Not every surface of your prototype needs to be perfect. If you are designing a game controller, the button layout and grip surfaces are critical — users will touch them. But the back panel? You can leave that as Lego.
The key finding from the study is what they call the 75% threshold. This is the balance point. If you cover more than 75% of the exterior surface with 3D-printed parts, you actually lose the time advantage compared to printing the whole thing at once. This happens because more 3D-printed surface means more internal interfaces between the printed shell and the Lego structure — and those interfaces require extra printing.
Below the 75% threshold, the savings grow quickly. At low fidelity levels — where most of the surface is Lego — the researchers measured fabrication time reductions of over 50%. So, the choice of which surfaces to print is not just an aesthetic decision. It is an engineering trade-off that directly affects how fast you can iterate.
The second approach solves a different problem: what if you split the 3D-printed parts and run them on multiple printers at the same time? Instead of one printer running for ten hours, you have five printers running for two hours each.
The results are positive, but with diminishing returns. The biggest jump comes from going from one printer to two — this gives roughly a 45% reduction in print time. Benefits continue to grow up to about six printers. After that, the gains are small. Beyond twelve printers, there is almost no benefit at all.
Why does it plateau? Because as you split the design into more parts, the assembly time grows. Also, if you have more printers than parts, the extra printers sit idle. So, there is an optimal number of printers for each prototype size, and it is usually lower than you might expect. The split lines between parts also affect visual quality, which matters depending on what you want to learn from the prototype.
The third strategy is perhaps the most interesting for teams that iterate over a long period. The idea is simple: when you update your design, you only reprint the parts that actually changed. The Lego internal structure stays the same. The unchanged 3D-printed panels stay the same. You only swap the panels that are different.
However, the benefit depends heavily on what kind of change you are making:
This tells us that component reuse is a strategy for the refinement phase. When the overall form is stable and you are tuning the details, each iteration becomes significantly cheaper. If you are still making fundamental design decisions, this approach does not help as much with time, though it still reduces material waste.
Knowing the three approaches is one thing. Implementing them is another. The researchers built an automated tool on top of Blender to handle the complex geometry work. The workflow has eleven steps:
This automation is what makes systematic comparison possible. Without it, setting up a hybrid prototype would be too time-consuming to be practical. With it, the engineering team can focus on what to build and why, not on the manual geometry work.
The authors tested their approaches on three physical products: a computer mouse, a game controller, and a digital camera. Each was prototyped at three fidelity levels — high (mostly printed), medium (about half printed), and low (mostly Lego visible). They also applied the method to a real product development project to validate the simulation findings.
The real-world results confirmed what the simulations showed. The benefits are real and measurable. The best results come when you choose the approach based on your current design goal:
The approaches are not mutually exclusive. The study suggests the maximum benefit comes from combining them — though a formal study of all combinations together is still needed.
For engineering managers and product leaders, the message is practical. The barrier to prototyping is real. It limits iteration, which limits learning, which limits the quality of the final product. Hybrid prototyping with Lego and 3D printing is not a trick or a workaround. It is a structured methodology with clear rules, measurable trade-offs, and an automated tool to support it.
The numbers from the paper — 56% time savings and 76% material savings — are not theoretical maximums. They are measured outcomes from real prototypes. The savings come not from lower quality, but from smarter allocation: high fidelity where it matters, speed and flexibility where it does not.
If your team is spending too much time waiting for prints, reprinting entire models after small changes, or avoiding prototyping because it is too expensive — this research gives a concrete answer to each of those problems.