Improving MRO order processing by means of advanced technological diagnostics and data mining approaches

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dc.identifier.uri http://dx.doi.org/10.15488/15978
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/16104
dc.contributor.author Seitz, Melissa
dc.contributor.author Lucht, Torben
dc.contributor.author Keller, Christian
dc.contributor.author Ludwig, Christian
dc.contributor.author Strobelt, Rainer
dc.contributor.author Nyhuis, Peter
dc.date.accessioned 2024-01-19T10:19:26Z
dc.date.available 2024-01-19T10:19:26Z
dc.date.issued 2020
dc.identifier.citation Seitz, M.; Lucht, T.; Keller, C.; Ludwig, C.; Strobelt, R. et al.: Improving MRO order processing by means of advanced technological diagnostics and data mining approaches. In: Procedia Manufacturing 43 (2020), S. 688-695. DOI: https://doi.org/10.1016/j.promfg.2020.02.121
dc.description.abstract Production planning based on uncertain load information may lead to low schedule adherence or low capacity utilization. Thus, maintenance, repair and overhaul (MRO) service providers are striving to improve their business processes to achieve high logistics efficiency. To estimate repair expenditures and material demands as early as possible, different approaches may be pursued. In this paper, the advancement of technological diagnostics to enable condition assessment without prior disassembly and the use of data mining to generate reliable forecasts are discussed. Thereby, the potential for planning MRO order processing is focused using the example of aircraft engines and rail vehicle transformers. eng
dc.language.iso eng
dc.publisher Amsterdam [u.a.] : Elsevier
dc.relation.ispartofseries Procedia Manufacturing 43 (2020)
dc.rights CC BY-NC-ND 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject Complex Capital Goods eng
dc.subject Condition Assessment eng
dc.subject Data Mining eng
dc.subject MRO eng
dc.subject Order Processing eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau
dc.title Improving MRO order processing by means of advanced technological diagnostics and data mining approaches eng
dc.type Article
dc.type Text
dc.relation.essn 2351-9789
dc.relation.doi https://doi.org/10.1016/j.promfg.2020.02.121
dc.bibliographicCitation.volume 43
dc.bibliographicCitation.firstPage 688
dc.bibliographicCitation.lastPage 695
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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