LiU Formula Student

We are proud sponsors of LiU Formula Student, a student association at Linköping University that designs a Formula Student car each year for international competitions against other student teams worldwide. The association comprises 120 volunteer students eager to learn the journey from CAD sketch to race-ready vehicle. 

Over the past year, we have had the opportunity to collaborate with William Gärefors, Head of Production at LiU Formula Student, who oversees production planning, procurement, and drawing reviews. William has driven the integration of our system as a standard step in the review process to streamline the team and reduce lead times. 

The association relies on continuous competence transfer, as the majority of members change annually. It is therefore crucial that this transfer happens efficiently, which also strengthens student engagement. 

As the sole final reviewer for a design team of 77 engineers, William’s reviews become a project bottleneck. Of the 1,100 drawings submitted each year, approximately half must be returned for correction. This creates unnecessary workload, stress, and long lead times, often resulting in weeks-long delays for the design team.

William has created custom review rules in our Studio, easily creating checks for common errors—such as incomplete drawing headers, incorrect axis references in 3D models, and misreferenced detail views. The review tool was then trained on the association’s own drawings and now reliably detects these issues. As William explains: 

“Our focus so far has been on identifying and creating rules for the everyday mistakes, errors that are trivial to fix but occur frequently and cause avoidable delays. Getting started with the Studio was simple since the training materials, example exercises, and explanatory texts make everything clear!”

The design team now uses AI Review during the design phase, enabling them to catch and correct errors before sending drawings to William for final approval. 

William highlights the pedagogical value of AI Review: 

“Receiving a clear report that pinpoints errors and explains their causes is incredibly valuable. It helps our junior engineers quickly understand and apply the design rules. I was initially concerned some might see it as an extra step, but once they realized the tool saves time and speeds up production, interest soared.”

When asked to estimate how much his own workload has changed, William shared: 

“Half of our submitted drawings contain various errors. AI Review now catches about 40 percentage points of these faults, saving a tremendous amount of time—both in my own review work and through shortened lead times. For 1,000 drawings, I can save roughly 33 hours of focused review time, nearly an entire workweek, assuming each drawing takes five minutes. That translates into several weeks of reduced lead time for our team.”

Beyond shorter lead times, William notes additional benefits: 

“With more efficient reviews, we can dedicate more time to value-adding activities such as production planning, training, and building a better car. AI Review has made the work more enjoyable and less stressful.” 

William sees great potential in the new analytics capabilities of AI Review Studio. These features will enable aggregated analyses of the team’s reviewed drawings and recurring errors, which can be used to enhance internal training and further improve drawing quality.