Prediction of temperature induced shape deviations in dry milling

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Denkena, B.; Schmidt, A.; Maaß, P.; Niederwestberg, D.; Niebuhr, C.; et al.: Prediction of temperature induced shape deviations in dry milling. In: Procedia CIRP 31 (2015), S. 340-345. DOI: https://doi.org/10.1016/j.procir.2015.03.072

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Sum total of downloads: 253




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Abstract: 
In this paper a model for a simulation based prediction of temperature induced shape deviations in dry milling is presented. A closed loop between Boolean material removal, process forces, heat flux and thermoelastic deformation is established. Therefore, an efficient dexel based machining simulation is extended by a contact zone analysis to model the local workpiece load. Based on the computed contact zone the cutting forces and heat flux are calculated using a semi-empirical process model. For a detailed consideration of the loads they are discretized and localized on the dexel-represented workpiece surface. A projection of the localized workpiece loads on the boundary of the finite element domain, taking into account the Boolean material removal during the process, allows the calculation of the current temperature and deformation of the workpiece. By transforming these thermomechanical characteristics back to the dexel-model a consideration in the machining simulation is possible. An extended contact zone analysis is developed for the prediction of the localized shape deviations. Finally, the results of the simulation are compared with measured data. The comparison shows that workpiece temperatures, workpiece deformation and shape deviations in different workpiece areas are predicted accurately.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2015
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 182 71.94%
2 image of flag of United States United States 23 9.09%
3 image of flag of China China 18 7.11%
4 image of flag of India India 4 1.58%
5 image of flag of Indonesia Indonesia 3 1.19%
6 image of flag of France France 3 1.19%
7 image of flag of Ukraine Ukraine 2 0.79%
8 image of flag of Greece Greece 2 0.79%
9 image of flag of Brazil Brazil 2 0.79%
10 image of flag of Botswana Botswana 1 0.40%
    other countries 13 5.14%

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