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System Development for the Configuration of Learning Factories

Kreß, Antonio and Metternich, Joachim (2020):
System Development for the Configuration of Learning Factories.
In: Procedia Manufacturing, 45. Elsevier B.V., pp. 146-151, ISSN 23519789,
DOI: 10.1016/j.promfg.2020.04.086,
[Article]

Abstract

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.

Item Type: Article
Erschienen: 2020
Creators: Kreß, Antonio and Metternich, Joachim
Title: System Development for the Configuration of Learning Factories
Language: English
Abstract:

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
Journal volume: 45
Publisher: Elsevier B.V.
Uncontrolled Keywords: Learning Factory, Factory Design, Axiomic Design, System Development, House of Quality
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: 04 May 2020 05:40
DOI: 10.1016/j.promfg.2020.04.086
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