Modeling of Workpiece Shape Deviations in face Milling of Parallel Workpiece Compounds

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Denkena, B.; Köhler, J.; Hasselberg, E.: Modeling of Workpiece Shape Deviations in face Milling of Parallel Workpiece Compounds. In: Procedia CIRP 8 (2013), S. 176-181. DOI: https://doi.org/10.1016/j.procir.2013.06.085

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Sum total of downloads: 12




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Abstract: 
The mass reduction of components is one of the most effective ways to reduce fuel consumption and emissions in the automotive and aircraft industry. A lightweight strategy used for highly loaded components is the combination of different materials to workpiece compounds. In that way components can be designed depending on the local load using the most qualified material. For the production of high-performance workpiece compounds high quality requirements concerning the accuracy of dimension and shape as well as surface roughness must be fulfilled. However, machining of workpiece compounds leads to unfavorable changes of the workpiece quality in comparison to machining of the single materials. Significant shape deviations occur when different materials are machined alternately in one cutting operation. This is due to unequal material properties, cutting characteristics, chip formation mechanisms as well as characteristic interactions between the single components. This paper describes the causes of the three main criteria material height deviation, transition deviation and surface roughness deviation that significantly influence the surface quality in parallel machining. The focus is on the process understanding as well as modeling of the surface defects. The approaches and results show that the characteristic shape deviations can be predicted. With the knowledge of the causes that lead to the surface defects in parallel machining it is possible to optimize the process setup for a surface quality oriented machining process of a workpiece compound. Copyright © 2013 Elsevier B.V.
License of this version: CC BY-NC-ND 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2013
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of United States United States 5 41.67%
2 image of flag of Germany Germany 4 33.33%
3 image of flag of Russian Federation Russian Federation 1 8.33%
4 image of flag of United Kingdom United Kingdom 1 8.33%
5 image of flag of China China 1 8.33%

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