Measures for Energy-Efficient Process Chains

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Denkena, B.; Dittrich, M.-A.; Kettelmann, S.; Reuter, L.: Measures for Energy-Efficient Process Chains. In: Procedia CIRP 98 (2021), S. 288-293. DOI: https://doi.org/10.1016/j.procir.2021.01.105

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/14342

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Sum total of downloads: 23




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Abstract: 
Energy efficiency is an essential factor for promoting sustainable manufacturing. Various types of energy consumption occur in modern process chains. This includes usage of electrical energy, e.g. for machine tools or air compression, but also energy consumption through use of resources (such as raw materials and supplies). In this paper, a process chain from the automotive industry is considered with the purpose of identifying energy saving potentials of various kinds. The process chain is used for the production of an axle component. In order to evaluate saving potentials, the current state of the process chain is analyzed. Then, the impact of process parameter optimization on the energy demand is examined. It was found that small energy savings through parameter optimization are possible. However, this can be problematic since process parameters are closely linked to process reliability, so energy savings might be achieved at the expense of product quality. Furthermore, it turns out that the reduction of the process energy is not sufficient for a broad energetic optimization of the process chain and base load reducing measures are required instead. Therefore, further analysis is focused on energetic effects of such measures as machine design, recycling, adjustments of process chain and product design. These were found to be an effective lever for minimizing energy demand of the process chain. A combination of feasible measures adds up to a potential energy saving of 11.5% in the investigated scenario.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of United States United States 9 39.13%
2 image of flag of Germany Germany 9 39.13%
3 image of flag of Israel Israel 3 13.04%
4 image of flag of Latvia Latvia 1 4.35%
5 image of flag of China China 1 4.35%

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