Generative Design In Factory Layout Planning: An Application Of Evolutionary Computing Within The Creation Of Production Logistic Concepts

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dc.identifier.uri http://dx.doi.org/10.15488/9656
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/9712
dc.contributor.author Dannapfel, Matthias
dc.contributor.author Vierschilling, Sebastian Patrick
dc.contributor.author Losse, Stephan
dc.contributor.author Matzke, Oliver
dc.date.accessioned 2020-03-16T15:21:39Z
dc.date.issued 2020
dc.identifier.citation Dannapfel, Matthias; Vierschilling, Sebastian Patrick; Losse, Stephan; Matzke, Oliver: Generative Design In Factory Layout Planning: An Application Of Evolutionary Computing Within The Creation Of Production Logistic Concepts. In: Nyhuis, P.; Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics : CPSL 2020. Hannover : publish-Ing., 2020, S. 147-156. DOI: https://doi.org/10.15488/9656 ger
dc.description.abstract This paper describes the creation and application of a generative design approach in the production logistics layout concept creation as part of factory planning projects. Production systems evermore are influenced by an increase of product variants during the planning stages as well as shorter replanning cycles due to higher agility requirements to the production system. Thus, requiring the planner to more frequently conduct the highly complex planning procedure of creating layout concepts for the material supply within the assembly line. Currently, mathematical or graphical assignment methods are executed but are often used disjunct and are not used jointly. Furthermore, today’s planning methods are mainly based on manual planning and assignment activities. To address the aforementioned issues, this paper elaborates the application and usability of generative design methods for production logistics planning. As first step the scope and requirements definition for the new production logistics layout application is conducted. Afterwards, generative design, including a multi-objective genetic algorithm, is used to serve as a solution to compile and search through the high-dimensional solution space of all possible logistic layout concepts. Here, layout restrictions and production goals, such as cost and time savings, are reconciled. After the design creation and evaluation by the algorithm, the planner overviews the results and enhances the design parameters until a final concept is reached. This paper concludes with a SWOT analysis of the new planning approach to investigate the used methods, evaluate the impact of the approach on planner’s work and identify additional research potentials of using the generative design for other factory planning domains. eng
dc.language.iso eng
dc.publisher Hannover : publish-Ing.
dc.relation.ispartof https://doi.org/10.15488/9640
dc.relation.ispartof Proceedings of the Conference on Production Systems and Logistics : CPSL 2020
dc.rights CC BY 3.0 DE
dc.rights.uri https://creativecommons.org/licenses/by/3.0/de/
dc.subject Generative design eng
dc.subject Multi-objective optimization eng
dc.subject Factory planning eng
dc.subject Production logistics planning eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.title Generative Design In Factory Layout Planning: An Application Of Evolutionary Computing Within The Creation Of Production Logistic Concepts
dc.type BookPart
dc.type Text
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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