Steps for Optimal Painting
Automated painting is a five-step process:
- First, a three-dimensional scan of the component is performed.
- Data from this scan forms the basis for a fluid dynamic simulation: Simulation software plots the trajectory of the paint particles and then determines the optimum volume of paint and air needed to achieve the required coating thickness.
- The system takes the simulation data to plan the most efficient robot path for the painting process. The optimal painting paths in the processing line are determined using intelligent algorithms and precise fluid dynamic flow simulations. Machine learning methods are used to optimize the path.
- The component is painted.
- Quality assurance check: Is the required coating thickness achieved?
Our part in the joint project is the three-dimensional scan of the component and the qualitiy assurance check with terahertz technology afterwards.
Three-Dimensional Object and Position Detection
In order for the painting cell to know the position of the object for simulation and painting, it must be recorded in three dimensions. The self-programming painting cell uses 3D sensors that were originally developed to control video games - a global mass market. The accuracy of the position detection is more exact than the deviations of common components from the CAD data and is therefore within the manufacturing and positioning tolerances. This high resolution is made possible by tailor-made algorithms for data processing.
Terahertz Technology for Quality Control
In the final process step of automated painting, the quality is checked: Is the thickness of the coating as desired? For this quality-control we use terahertz waves. With this technology developed by us wet and coloured lacquers can be measured without contact. The quality of the paint layers can already be checked during or after the painting process. Substrates - the basis of the coating layers - do not have to be metallic, but can also consist of other materials.