Stock market related pricing mechanisms for the tool and mould manufacturing industry

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Denkena, B.; Nemeti, A.: Stock market related pricing mechanisms for the tool and mould manufacturing industry. In: Procedia CIRP 12 (2013), S. 414-419. DOI: https://doi.org/10.1016/j.procir.2013.09.071

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/992

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Sum total of downloads: 230




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Abstract: 
Tool and mould manufacturers typically prepare their quotation provide an accurate price of, for example, a die casting mould is a key competitive factor for such companies. However, particularly in the customised production area, calculating the quotations and tenders has been proven as extremely challenging and subjective matter. One main cause is that time dynamic costs are rarely taken into consideration sufficiently even though they have a major impact on the final quotation due to the large time frame between the moment of the initial quotation and the actual production start. They neglect can lead to a significant discrepancy of up to 40 percent between pre- And post-calculation and thus to a loss of the corporate added value. A novel method developed at the Institute of Production Engineering and Machine Tools (IFW), Leibniz Universität Hannover, aims to provide a framework which allows tool and mould manufacturer to prepare a more precise and reliable quotation by taking time-dependent dynamic costs into consideration. The prediction of the time dynamic costs takes place by using stock market pricing mechanisms. Subsequently, based on enterprise related knowledge aggregation, this method also accounts for the probability of occurrence of each quotation thereby minimising the discrepancy between the pre- and post-calculation.
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 166 72.17%
2 image of flag of United States United States 31 13.48%
3 image of flag of China China 9 3.91%
4 image of flag of Indonesia Indonesia 4 1.74%
5 image of flag of South Africa South Africa 3 1.30%
6 image of flag of Russian Federation Russian Federation 3 1.30%
7 image of flag of Namibia Namibia 3 1.30%
8 image of flag of No geo information available No geo information available 2 0.87%
9 image of flag of Ukraine Ukraine 1 0.43%
10 image of flag of Pakistan Pakistan 1 0.43%
    other countries 7 3.04%

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