Optimizing NC-tool paths for simultaneous five-axis milling based on multi-population multi-objective evolutionary algorithms
Computer-Numerical-Control based five-axis milling offers new possibilities for improving the machining process. However, this procedure is still difficult to handle, particularly in case of machining complex free-formed surfaces. An optimization approach based on the multi-objective evolutionary algorithm SMS-EMOA (S-metric selection evolutionary multi-objective optimization algorithm) combined with a multi-population approach has been developed and used in order to utilize the potential of the five-axis milling process. After a general introduction to this machining process and the potential of path optimization, the designed multi-population multi-objective evolutionary approach, its integration into the simulation, and its adaptation to the practical example is described.
five-axis milling evolutionary algorithm multi-objective optimization engineering