Geometrical process design during continuous generating grinding of cutting tools

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Denkena, B.; Bergmann, B.; Theuer, M.; Wolters, P.: Geometrical process design during continuous generating grinding of cutting tools. In: The International Journal of Advanced Manufacturing Technology 121 (2022), Nr. 5-6, S. 3871-3882. DOI: https://doi.org/10.1007/s00170-022-09573-7

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/14672

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Sum total of downloads: 51




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Abstract: 
Modern cutting tools like end mills, drilling tools, and reamers underlie high requirements regarding geometrical accuracy, cutting edge quality, and production costs. However, the potential for process optimization is limited due to the process kinematics during grinding. Consequently, a novel tool grinding process for the manufacture of cutting tools has been developed recently at the Institute for Production Engineering and Machine Tools (IFW). This continuous generating grinding process allows the simultaneous production of all flutes and circumferential flank faces of rotational symmetrical cutting tools. The present paper focuses on the geometrical process design and develops a method to determine the necessary basic rack and process parameters in order to create a desired cutting edge geometry by continuous generating grinding. The developed method can define all parameters with an accuracy of up to 5 µm and 0.2° within a simulation in five iteration steps and allows not only the quantitative design of the cutting tool geometry but a qualitative modification of the flute geometry as well. Subsequently performed grinding tests showed that the presented method allows the design of grinding worms for continuous generating grinding of cutting tools and enables the successful implementation of these processes.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 32 62.75%
2 image of flag of United States United States 9 17.65%
3 image of flag of Belgium Belgium 3 5.88%
4 image of flag of Turkey Turkey 2 3.92%
5 image of flag of Czech Republic Czech Republic 2 3.92%
6 image of flag of Indonesia Indonesia 1 1.96%
7 image of flag of China China 1 1.96%
8 image of flag of Switzerland Switzerland 1 1.96%

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