Robust multi-objective optimization in product development with respect to user-scenario and manufacturing uncertainties

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Wolniak, P.; Cramer, J.; Lachmayer, R.: Robust multi-objective optimization in product development with respect to user-scenario and manufacturing uncertainties. In: Proceedings of the Design Society 1 (2021), S. 2591-2600. DOI: https://doi.org/10.1017/pds.2021.520

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/16762

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Sum total of downloads: 8




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Abstract: 
In product development, user-scenarios are a way of tailoring requirements to defined customer groups. Furthermore, a product design often involves multiple conflicting objectives that are analyzed within an iterative process. The models typically used for the analysis often do not accurately reflect the real-world representation. This can be alleviated by finding robust product designs. While usually uncertainties due to manufacturing tolerances are investigated, we additionally consider uncertainties in the user-scenario. Therefore, we present a robustness evaluation in a multi-objective numerical optimization in product development. For this, we consider manufacturing tolerances using an adjusted Latin Hypercube Sampling as well as deviations in the user-scenario by means of a Gaussian distribution. In the case study, we present the robust development of a customer specific coffee machine, where we show the robustness evaluation and the impact of the proposed adjustments. The advantage of the presented process is a product design tailored to the customer's requirements under specified uncertainties. In addition, this enables a time benefit in the product development due to the automated analysis used in the optimization.
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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1 image of flag of United States United States 4 50.00%
2 image of flag of Germany Germany 4 50.00%

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