Energy-efficient control of dust extraction for the machining of fibre-reinforced plastics

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Denkena, Berend; Bergmann, Benjamin; Rahner, Björn-Holger: Energy-efficient control of dust extraction for the machining of fibre-reinforced plastics. In: Procedia CIRP 78 (2018), S. 49-54. DOI: https://doi.org/10.1016/j.procir.2018.08.178

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/5175

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Sum total of downloads: 73




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Abstract: 
Fibre-reinforced plastics (FRPs) are becoming increasingly important in aerospace and automotive applications. However, dry machining of FRPs generates abrasive and electrically conductive dust particles that can furthermore cause explosive dust-air mixtures in the enclosed workspace of the machine tool. In order to protect the machine operator and the machine tool, powerful extraction systems (engine power > 5 kW) are usually installed and operated with a constant flow rate, resulting in a significant increase of the machine tool’s overall energy requirement. This paper introduces a novel approach for a demand-oriented control of the flow rate to increase the energy efficiency of dust extraction systems. The objective of the developed control mechanisms is to maintain the maximum permissible dust limit with minimum energy demand. A low-cost dust sensor serves as a feedback system for the applied control mechanism. In a further stage, a force measuring platform was added to provide additional signals for an increased performance of the controlled system. To evaluate the presented approach, milling tests were carried out with carbon-fibre-reinforced plastic (CFRP). The experimental results show that the energy requirement can be reduced by up to 70%.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2018
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 43 58.90%
2 image of flag of United States United States 13 17.81%
3 image of flag of China China 6 8.22%
4 image of flag of Russian Federation Russian Federation 2 2.74%
5 image of flag of Poland Poland 2 2.74%
6 image of flag of Taiwan Taiwan 1 1.37%
7 image of flag of Latvia Latvia 1 1.37%
8 image of flag of Kenya Kenya 1 1.37%
9 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 1.37%
10 image of flag of United Kingdom United Kingdom 1 1.37%
    other countries 2 2.74%

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