Improving the Processing Efficiency of Redundant Galvanometer Scanner-Based Systems by Optimising the Processing Order of Geometries in a CAM Tool

The combination of highly dynamic systems with a limited work envelope, with a less dynamic system with a larger working envelope, promises to combine the advantages of both systems while eliminating the disadvantages. For these systems separation algorithms determine the trajectories based on the target geometries. However, arbitrary processing orders of these result in inefficient trajectories because successive geometries maybe geometrically far apart. This causes the dynamic system to operate below its potential. Current planning tools do not optimise the processing order for such redundant systems. The aim is to design and implement a planning tool, for the application of laser marking. The tool considers the processing order of the 2D geometries from a geometric point of view. The resulting sequenced path data can then be used by trajectory generation algorithms to make full use of the potential of redundant systems. The approach analyses literature on Travelling Salesman Problems (TSP), which is then transferred to the given application. A heuristic and a genetic algorithm are developed and integrated into a planning tool. The results show the heuristic algorithm being faster, while still producing solutions whose total path length is similar to that of the genetic algorithm. Even though, the solutions don’t meet any optimality standards, the presented automated approaches are superior to manual approaches and are to be seen as a starting point for further research.