Model-based Analysis of Reassembly Processes within the Regeneration of Complex Capital Goods

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Kuprat, T.; Schmidt, M.; Nyhuis, P.: Model-based Analysis of Reassembly Processes within the Regeneration of Complex Capital Goods. In: Procedia CIRP 55 (2016), S. 206-211. DOI: https://doi.org/10.1016/j.procir.2016.08.008

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Sum total of downloads: 8




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Abstract: 
In regenerating complex capital goods two of the key criteria for success on the market include keeping downtimes to a minimum in order to realize short throughput times and maintaining a high degree of schedule reliability. When unable to comply with the market's demands on their logistical performance, companies that provide regeneration services are faced with significant financial penalties and costs for delays as well as the threat of customers switching to competitors. In addition, regeneration processes must be economically effective. Efficiently designing and planning the entire regeneration process is therefore indispensable. As a core element, the reassembly at the end of the process chain plays a key role. Since the various material flows merge together here, the logistic quality of the supply processes is particularly visible at this point. Furthermore, reassembly is generally the last value-adding process within the regeneration supply chain. Up until now, descriptive and analytical approaches consider the various supply processes independently of one another and ignore to some degree existing statistical dependencies between these processes. These dependencies however, are frequently found in the industry and have to be taken into consideration when planning tasks and evaluating design measures. This paper will thus introduce the different existing approaches for describing and analyzing reassembly processes and compare them using a case study.
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

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pos. country downloads
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1 image of flag of United States United States 4 50.00%
2 image of flag of Netherlands Netherlands 2 25.00%
3 image of flag of Germany Germany 2 25.00%

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