Online adaption of milling parameters for a stable and productive process
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Date
2021
Authors
Volume
70
Issue
1
Journal
CIRP Annals - Manufacturing Technology
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Publisher
Paris : CIRP
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Abstract
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.
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CC BY-NC-ND 4.0 Unported