Coding enables robotics for additive manufacturing
2 mins to read
During the recent coding day in Paris, experts from Montimage, Norce, IBM, IRT, SINTEF and CROOM worked together on advancing a solution involving robotics. Additive manufacturing of medical implants requires highly sophisticated post-processing to make sure no sharp edges remain, which could potentially damage tissue later on at any point – a process which is hard to automate. Complexity increases with patient-specific implants since every person has a unique geometry.
Need for precision and adaptability
To automate the post-processing of medical implants, there is a need to create a seamless system that integrates several components, such as a robotic gripper, vision systems and digital twins. The challenge lies in ensuring all parts work together effectively while maintaining precision and adaptability.
The team focused on improving workflows and addressing issues like trajectory planning, tool design and automating key processes. By refining these elements, they aim to create a more efficient and reliable system.
Deep tech coming to life
Key activities included linking High-Resolution Layers (HRLs) to subtasks and integrating feedback from digital twins. The team also worked on improving the vision system, exploring techniques such as backlight scanning to eliminate motion blurring and tools like Meshroom, which can translate two-dimensional photos into 3D.
The team also improved the Human-Machine Interface (HMI) to make it more user-friendly. They designed the interface with three levels of functionality:
- Read/edit for system adjustments
- Read-only for basic viewing
- Data analysis for insights
Streamlining collaboration with tools
The team used GitHub and Microsoft Azure DevOps to manage the project and track progress. These tools allowed the team to:
- Collaborate on code and track changes
- Organise tasks and monitor workflows
- Adjust approaches quickly as new insights emerged
What’s next?
The next steps include testing the refined solutions in real-world conditions and continuing to enhance the integration of key components.
For CROOM, these efforts bring them closer to deploying a fully functional system that addresses the challenges of automation and system integration practically and efficiently.