Tisch, Michael ; Laudemann, Heiko ; Kreß, Antonio ; Metternich, Joachim (2017)
Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem.
In: Procedia Manufacturing, 7th Conference on Learning Factories, Darmstadt, Elsevier B.V., 9
doi: 10.1016/j.promfg.2017.04.017
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
The paper presents a structural approach to configure the technical system of a learning factory by considering learning targets and maximizing the utility. Local scope conditions and intended competencies are used to operationalize requirements. The composition of the module-based technical system can be optimized by maximizing its overall utility. Therefore, an exact and efficient optimization algorithm is developed solving a multidimensional multiple-choice knapsack problem combined with a two-dimensional bin packing problem. Restrictions are the available budget and the useable area of the learning factory. As a result, the configured technical system enables optimal target orientation of the learning factory. This procedure is finally applied on the Process Learning Factory CiP.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Tisch, Michael ; Laudemann, Heiko ; Kreß, Antonio ; Metternich, Joachim |
| Art des Eintrags: | Bibliographie |
| Titel: | Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem |
| Sprache: | Englisch |
| Publikationsjahr: | 2017 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia Manufacturing, 7th Conference on Learning Factories, Darmstadt, Elsevier B.V. |
| Jahrgang/Volume einer Zeitschrift: | 9 |
| DOI: | 10.1016/j.promfg.2017.04.017 |
| URL / URN: | https://doi.org/10.1016/j.promfg.2017.04.017 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | The paper presents a structural approach to configure the technical system of a learning factory by considering learning targets and maximizing the utility. Local scope conditions and intended competencies are used to operationalize requirements. The composition of the module-based technical system can be optimized by maximizing its overall utility. Therefore, an exact and efficient optimization algorithm is developed solving a multidimensional multiple-choice knapsack problem combined with a two-dimensional bin packing problem. Restrictions are the available budget and the useable area of the learning factory. As a result, the configured technical system enables optimal target orientation of the learning factory. This procedure is finally applied on the Process Learning Factory CiP. |
| Freie Schlagworte: | learning factory, technical system, competency development |
| 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: | 01 Sep 2017 11:28 |
| Letzte Änderung: | 02 Jul 2024 14:52 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
-
Utility-based configuration of learning factories using a multidimensional, multiple-choice knapsack problem. (deposited 19 Jun 2024 14:56)
- Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem. (deposited 01 Sep 2017 11:28) [Gegenwärtig angezeigt]
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum