The researchers are currently exploring a fused deposition model. In this additive process, thin strands of molten plastic are superimposed layer by layer.
Even before the 3D printing process begins, the expert system that the researchers seek is supposed to provide recommendations on which material, which layer thickness, and which layer orientation are best suited to achieve the highest possible transmission or the highest possible permeability for the laser. With this preliminary work, it will be possible to weld the printed components.
Additionally, the scientists want to develop a method to evaluate transmission with spatial resolution. This involves determining (for an individual component) at which points the laser beam is transmitted, and to what extent. That data will then be used to control the laser transmission welding process with the help of the expert system. If the laser is less transmitted at a certain point, for example, laser power would be increased. If the component is more light-transmissive at another point, a lower power would be used. This adaptive system would enable a uniform weld seam, even if the component itself is not uniform in terms of its transmission.
The team is eyeing machine learning methods to process the information, and, more specifically, neural networks. This will enable the system to learn to recognize correlations between various input variables and the print result independently, and thus predict the expected transmission.
The project is funded by the German Federal Ministry for Economic Affairs and Energy.