Software tools for very high deposition rate additive manufacturing

Important results from the project

The project has resulted in faster and more robust software based on smaller and decoupled software modules written in Rust. This change has led to a better product architecture that is designed to interact with AI agents, machine vision or other future software tools. Interviews have validated that the interest from the industry is extensive and that there are several conceivable business models. The project has also led to a significant order through a collaboration partner.

Expected long term effects

The software is expected to become the foundation for a new company or business unit within Procada. The team is convinced that the need for high-performance data logging functionality is becoming increasingly important as AI usage increases. Sådan AI requires large amounts of process information, specific to factories and machines. The developed tool can enable this and help companies collect and interpret data for more efficient production.

Approach and implementation

When the intended developer resource made it clear late in the process that they would not be able to participate in the project to a sufficient extent, the project needed to be restructured to rely more on Procada´s own staff for development. To compensate for this, an LIA student was attached to the project who, after training and under supervision, was able to complete most of the tasks. A business development and marketing consultant was used to conduct interviews with around twenty actors.