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Originalpublikation
Bergmann, B.; Reimer, S.: Online adaption of milling parameters for a stable and productive process. In: CIRP Annals - Manufacturing Technology 70 (2021), Nr. 1, S. 341-344. DOI: https://doi.org/10.1016/j.cirp.2021.04.086
On the way to fully autonomous machine tools it is essential to independently select suitable process parameters and adapt them on-the-fly to the appropriate process conditions in a self-controlled manner. Such systems require complex physical process models and are usually limited to feed and spindle speed adaption during the milling process. This paper introduces a new approach enabling machines during the milling process to learn which parameters lead to a stable process with maximum productivity and to adjust them autonomously. It is shown that this approach enables the machine tool to independently find stable process parameters with maximum productivity.