Starting from the component’s digital model, the system autonomously guides the robot to scan surfaces without interrupting production. It positions itself, captures data and calculates the tapering angle, a key indicator of coating quality. Deviations are detected in real time, enabling immediate action to reduce defects and waste.
“Our solution is fully automated and requires no manual programming,” says Michele Foletti, researcher at the SPS Laboratory. “It achieves an accuracy of up to 0.1 degrees on the tapering angle and can measure full cycles in under three seconds. It is also scalable and compatible with different industrial robots and 3D sensors, adapting to complex geometries and component types.”
The system has been tested on coatings produced with cold spray, a process that deposits high-velocity metal particles to form protective layers on surfaces exposed to wear or corrosion. Early applications include aerospace components, heat exchangers for domestic heating and parts for electric mobility, where lightweight design and thermal efficiency are critical.
The work is part of the SURE2COAT (Sustainable Surface Treatments of Complex Shape Components for Transsectorial Industrial Innovation) project, which promotes the use of lightweight alloys for complex components and new industrial applications. Interest in alternatives to steel, such as aluminium, is increasing to reduce weight and costs. However, these materials require advanced surface treatments to withstand corrosion in demanding environments.
SUPSI contributes by supporting the transfer of these technologies to industry, integrating quality control systems directly into production lines. “Robotics and computer vision systems can make production more efficient and sustainable,” adds Foletti, “supporting the transition from research to smart manufacturing.”
Next developments aim to make the system self-correcting, enabling it not only to measure coatings but also to adjust parameters such as robot speed, powder flow and nozzle distance in real time, with the goal of further reducing production waste.