Simulation based parameterization for process monitoring of machining operations

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Denkena, B.; Koeller, M.: Simulation based parameterization for process monitoring of machining operations. In: Procedia CIRP 12 (2013), S. 79-84. DOI: https://doi.org/10.1016/j.procir.2013.09.015

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/988

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Sum total of downloads: 205




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Abstract: 
Process monitoring can prevent machine and tool failure in metal-cutting. A successful process monitoring of cutting processes depends on reliable monitoring limits for the process. In industrial applications these limits have to be generated in a learning phase during a ramp-up process. In order to enable process monitoring for single batch production without a learning phase, this paper describes a simulation based approach for generating reference data to set process limits. As a foundation for calculation of monitoring limits a position-based process simulation has to be established. In a first step an approach of modeling material removal is evaluated to check whether it fits the application for parameterizing the process monitoring. In this context the potentials of a process simulation for calculating process limits are clarified. Additionally the quality of data generated by this kind of simulation is discussed. In a second step a method is described to implement machine properties by a virtual machine tool within a simulation of material removal. For that purpose a method to use actual data of axis position and tool within the simulation of material removal is necessary. With these data a way-based simulation of material removal can generate reference parameters for monitoring limits instead of using data from a learning phase during the ramp-up process. By using position data of a virtual machine tool a reliable source for the actual position of all axes enables the position-based simulation to perform material removal in a more accurate way.
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

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 147 71.71%
2 image of flag of United States United States 19 9.27%
3 image of flag of China China 16 7.80%
4 image of flag of No geo information available No geo information available 4 1.95%
5 image of flag of Namibia Namibia 3 1.46%
6 image of flag of Austria Austria 3 1.46%
7 image of flag of Brazil Brazil 2 0.98%
8 image of flag of Japan Japan 1 0.49%
9 image of flag of India India 1 0.49%
10 image of flag of Indonesia Indonesia 1 0.49%
    other countries 8 3.90%

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