An Approach to describe Gentelligent Components in their Life Cycle

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Lachmayer, R.; Mozgova, I.; Scheidle, W.: An Approach to describe Gentelligent Components in their Life Cycle. In: Procedia Technology 26 (2016), S. 199-206. DOI: https://doi.org/10.1016/j.protcy.2016.08.027

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/3228

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Sum total of downloads: 108




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Abstract: 
Information about products and their life cycle are often required for the product development and manufacturing process. So the application of life cycle data of smart products offers new opportunities to pass information to a new product generation. In the Collaborate Research Center (CRC) 653 smart products, so called “Gentelligent Components”, which collect information about themselves and from their life cycle and store it inherently, are developed. For structuring and standardization of the life cycle information a classification system is used. A classification system for gentelligent components has to consider aspects from the development, manufacturing and usage phases as well as the environment and also the remaining life cycle phase. Therefore different classification systems are compared to their suitability for gentelligent components. Based on the most suitable existing system an approach to describe gentelligent components in their life cycle is developed. The information from development and manufacturing as well as from the usage phase of components life cycle are considered. The resulted classification system is exemplified by a wheel carrier, one of the demonstrator of the CRC 653. The applied classification system shows how gentelligent components and their information can be structured and standardized.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2016
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 82 75.93%
2 image of flag of United States United States 9 8.33%
3 image of flag of United Kingdom United Kingdom 3 2.78%
4 image of flag of China China 3 2.78%
5 image of flag of No geo information available No geo information available 1 0.93%
6 image of flag of Turkey Turkey 1 0.93%
7 image of flag of Sweden Sweden 1 0.93%
8 image of flag of Namibia Namibia 1 0.93%
9 image of flag of Italy Italy 1 0.93%
10 image of flag of Hong Kong Hong Kong 1 0.93%
    other countries 5 4.63%

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