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dc.contributor.authorWaldburger, Raoul
dc.date.accessioned2021-02-16T07:33:00Z
dc.date.available2021-02-16T07:33:00Z
dc.date.issued2021-02-03
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/32164
dc.identifier.urihttp://dx.doi.org/10.26041/fhnw-3664
dc.description.abstractSRS-4-MSE is focusing on a process-centric scheduling for MSE in the MEM sector by combining process mining and process simulation algorithms in a recommender system to reduce throughput times with the application of a digital twin. In the Swiss mechanical and electrical engineering industries (MEM), usually ERP modules for scheduling processes based on heuristics are applied in the production planning. Reduction of throughput time with smart digital twins in the production allows for an increase regarding flexibility and responsiveness as well as higher delivery readiness (reduced out-of-stock). First analysis results of the PoC performed with an anonymized offline data set indicated a reduction potential of average throughput times of over 50%.en_US
dc.description.urihttps://www.industrie2025.ch/veranstaltungen/fe-konferenz-zu-industrie-40en_US
dc.language.isode_CHen_US
dc.relation.ispartofseriesIndustrie 2025;
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.accessRightsAnonymous*
dc.subjectProduction planningen_US
dc.subjectProcess miningen_US
dc.subject.ddc600 - Technik, Medizin, angewandte Wissenschaftenen_US
dc.titleSmart scheduling recommender system for process-centric production planning in medium sized enterprises (SRS-4-MSE)en_US
dc.type06 - Präsentation*
dc.spatialOnline-Konferenzen_US
dc.event6. F&E-Konferenz zu Industrie 4.0en_US
dc.audiencePraxisen_US
fhnw.publicationStateUnpublisheden_US
fhnw.ReviewTypeAnonymous ex ante peer review of an abstracten_US
fhnw.InventedHereYesen_US
fhnw.PublishedSwitzerlandYesen_US
fhnw.IsStudentsWorknoen_US


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