Abstract
The acquisition of in-process measurement data for the optimization of machined components is carried out using various analysis methods. Depending on the required information content, investigations are usually made by specialized production engineers. However, due to the complex interrelationships of different process parameters, an optimization must be carried out under real production conditions. In order to achieve this, process optimizations performed on a milling machine are presented, which are carried out by means of machine-internal sensor technology. For use in the industrial environment, the user-oriented processing of measurement data is a decisive requirement. The combination of machine-internal measured values and additional machine parameters enables an efficient and objective process optimization by qualified skilled workers on workshop level. This enables significant energy savings in the metal cutting industry.
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Acknowledgments
This research project is funded by the Gesellschaft für Energie- und Klimaschutz Schleswig-Holstein GmbH (EKSH) under project 8/12-45.
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Gericke, T., Mattes, A., Overhoff, B., Rost, L. (2021). User-Centered Optimization System at Workshop Level for More Energy-Efficient Machine Tool Operations. In: Ahram, T., Taiar, R., Groff, F. (eds) Human Interaction, Emerging Technologies and Future Applications IV. IHIET-AI 2021. Advances in Intelligent Systems and Computing, vol 1378. Springer, Cham. https://doi.org/10.1007/978-3-030-74009-2_43
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DOI: https://doi.org/10.1007/978-3-030-74009-2_43
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