Evolutionary Approach for an Optimized Analysis of Product Life Cycle Data

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dc.identifier.uri http://dx.doi.org/10.15488/3212
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/3242
dc.contributor.author Lachmayer, Roland
dc.contributor.author Mozgova, Iryna
dc.contributor.author Sauthoff, Bastian
dc.contributor.author Gottwald, Philipp
dc.date.accessioned 2018-05-04T12:29:21Z
dc.date.available 2018-05-04T12:29:21Z
dc.date.issued 2014
dc.identifier.citation Lachmayer, R.; Mozgova, I.; Sauthoff, B.; Gottwald, P.: Evolutionary Approach for an Optimized Analysis of Product Life Cycle Data. In: Procedia Technology 15 (2014), S. 359-368. DOI: https://doi.org/10.1016/j.protcy.2014.09.090
dc.description.abstract The application of life cycle data of smart products offers new opportunities for the product development process. Nowadays, products often consist of adaptive design variants of an existing product. Taking this into account, the new product development approach called technical inheritance is developed analogous to biological inheritance. This approach considers the intergenerational evolution of design characteristics. Enhanced smart products are developed within the Collaborate Research Center (CRC) 653 called “Gentelligent Components in Their Lifecycle”. These features the capabilities to sense, collect and transfer life cycle data inherently by using genetic product properties and artificial intelligence. By using technical inheritance optimization strategies are currently investigated and the design of gentelligent components is researched. During the technical inheritance various monitoring concepts are applied to realize a targeted algorithmic feedback of lifecycle information from smart products. For a targeted algorithmic feedback of product life cycle information methods of data mining are applied. These include the objectives of data beneficiation as well as information detection. The boundaries of the investigations are determined through the gentelligent components. Therefore highly mechanical loaded systems are in focus. It follows that the physical aspects and specific life cycle incidents are major objects for the monitoring concept of the product life cycle. The approach aims at the integration of an evolutionary algorithm to identify the component specific critical loads as well as the optimal allocation of loads cases. The results of this concept are exemplified by a wheel suspension which is part of the demonstrator of collaborate research center. eng
dc.language.iso eng
dc.publisher Amsterdam : Elsevier
dc.relation.ispartofseries Procedia Technology 15
dc.rights CC BY-NC-ND 3.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject Data Mining eng
dc.subject Life Cycle Information eng
dc.subject Evolutionary Algorithm eng
dc.subject.ddc 600 | Technik ger
dc.title Evolutionary Approach for an Optimized Analysis of Product Life Cycle Data
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2212-0173
dc.relation.doi https://doi.org/10.1016/j.protcy.2014.09.090
dc.bibliographicCitation.volume 15
dc.bibliographicCitation.firstPage 359
dc.bibliographicCitation.lastPage 368
dc.description.version publishedVersion
tib.accessRights frei zug�nglich

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