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System development for the configuration of learning factories

Kreß, Antonio ; Metternich, Joachim (2020):
System development for the configuration of learning factories. (Publisher's Version)
In: Procedia Manufacturing, 45, pp. 146-151. Elsevier, ISSN 2351-9789,
DOI: 10.25534/tuprints-00014280,

Copyright Information: CC-BY-NC-ND 4.0 International - Creative Commons, Attribution NonCommercial, NoDerivs.

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Item Type: Article
Origin: Secondary publication service
Status: Publisher's Version
Title: System development for the configuration of learning factories
Language: English

Learning factories represent realistic learning environments for academia and industry in order to develop competencies. The design of learning factories can be facilitated by a configuration system. The configuration of a learning factory describes the selection of factory elements and products. Mathematically this selection can be described by an optimization problem based on a utility function and restrictions. Optimization algorithms facilitate the planning process by selecting the feasible combination of factory elements with the highest utility. This paper describes the methodology to develop a configuration system for learning factories. Customer needs for the configuration system were identified by an explorative stakeholder study: Learning factory developers, operators, and trainers were interviewed with open and partially open questions. These customer needs were then evaluated regarding their importance. The relationship between customer needs and functional requirements is described in a House of quality. To determine the system design systematically, the decomposition principle and the zig-zag process of the Axiomatic Design were applied. Axiomatic Design is a method to design engineering systems including complex systems and software. Consequently, the functional requirements were transformed into design parameters. Design parameters characterize the design of the configuration system.

Journal or Publication Title: Procedia Manufacturing
Volume of the journal: 45
Publisher: Elsevier
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > CiP Center for industrial Productivity
Date Deposited: 30 Nov 2020 14:31
Last Modified: 30 Nov 2020 14:31
DOI: 10.25534/tuprints-00014280
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-142801
Additional Information:

10th Conference on Learning Factories, CLF2020

URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/14280
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