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Procedure for the configuration of learning factories: Application in industry and comparison

Kreß, Antonio ; Metternich, Joachim (2022)
Procedure for the configuration of learning factories: Application in industry and comparison.
12th Conference on Learning Factories (CLF 2022). Singapore (11.-13.04.2022)
doi: 10.2139/ssrn.4071863
Konferenzveröffentlichung, Bibliographie

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Kurzbeschreibung (Abstract)

During the design of learning factories, the configuration of the technical system plays an important role. The selection of factory elements for learning factories usually takes place based on intuition. Intuitive selection has the disadvantage that the best possible selection is only achieved by chance. In this paper, a method is presented that is based on solving an optimisation problem, which ensures the best possible selection of factory elements considering a target function with restrictions like the budget or the usable area. For this purpose, four steps are distinguished: First, requirements for the technical configuration are derived from the primary goals of the learning factory (step I). Then, factory areas and configuration alternatives containing a combination of factory elements are derived from the products and processes (step II). The utility values of the potential configuration alternatives are determined based on an evaluation method (step III). Subsequently, the best possible combination of configuration alternatives is determined algorithmically by solving an optimisation problem (step IV). This procedure extends the design approach of Abele et al. (2019). It is applied to a learning factory for a company in the mobility industry to evaluate its superiority to an intuitive approach.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Kreß, Antonio ; Metternich, Joachim
Art des Eintrags: Bibliographie
Titel: Procedure for the configuration of learning factories: Application in industry and comparison
Sprache: Englisch
Publikationsjahr: 2022
Ort: Darmstadt
Verlag: SSRN - Elsevier
Buchtitel: Proceedings of the 12th Conference on Learning Factories (CLF 2022)
Kollation: 6 Seiten
Veranstaltungstitel: 12th Conference on Learning Factories (CLF 2022)
Veranstaltungsort: Singapore
Veranstaltungsdatum: 11.-13.04.2022
DOI: 10.2139/ssrn.4071863
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Kurzbeschreibung (Abstract):

During the design of learning factories, the configuration of the technical system plays an important role. The selection of factory elements for learning factories usually takes place based on intuition. Intuitive selection has the disadvantage that the best possible selection is only achieved by chance. In this paper, a method is presented that is based on solving an optimisation problem, which ensures the best possible selection of factory elements considering a target function with restrictions like the budget or the usable area. For this purpose, four steps are distinguished: First, requirements for the technical configuration are derived from the primary goals of the learning factory (step I). Then, factory areas and configuration alternatives containing a combination of factory elements are derived from the products and processes (step II). The utility values of the potential configuration alternatives are determined based on an evaluation method (step III). Subsequently, the best possible combination of configuration alternatives is determined algorithmically by solving an optimisation problem (step IV). This procedure extends the design approach of Abele et al. (2019). It is applied to a learning factory for a company in the mobility industry to evaluate its superiority to an intuitive approach.

Freie Schlagworte: learning factory design, design approach, optimisation, decision making
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
600 Technik, Medizin, angewandte Wissenschaften > 670 Industrielle und handwerkliche Fertigung
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW)
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > CiP Center für industrielle Produktivität
Hinterlegungsdatum: 02 Aug 2024 12:54
Letzte Änderung: 02 Aug 2024 12:54
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