Tisch, Michael ; Laudemann, Heiko ; Kreß, Antonio ; Metternich, Joachim (2017):
Utility-based configuration of learning factories using a multidimensional, multiple-choice knapsack problem. (Publisher's Version)
In: Procedia Manufacturing, 9, pp. 25-32. ISSN 2351-9789,
DOI: 10.25534/tuprints-00014287,
[Article]
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.
| Item Type: | Article |
|---|---|
| Erschienen: | 2017 |
| Creators: | Tisch, Michael ; Laudemann, Heiko ; Kreß, Antonio ; Metternich, Joachim |
| Origin: | Secondary publication service |
| Status: | Publisher's Version |
| Title: | Utility-based configuration of learning factories using a multidimensional, multiple-choice knapsack problem |
| Language: | English |
| 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. |
| Journal or Publication Title: | Procedia Manufacturing |
| Volume of the journal: | 9 |
| Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > CiP Center for industrial Productivity |
| Date Deposited: | 30 Nov 2020 14:45 |
| DOI: | 10.25534/tuprints-00014287 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/14287 |
| URN: | urn:nbn:de:tuda-tuprints-142879 |
| Additional Information: | 7th Conference on Learning Factories, CLF 2017 |
| PPN: | |
| Corresponding Links: | |
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