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Competence development for collaborative work systems in learning factories

  • Shorter product life cycles and emerging technologies are changing the circumstances under which the design of assembly and logistics systems has to be carried out. Engineers are in charge of adapting the production in accordance with the underlying product at a higher pace, oversee a more complex system and find the ideal solution for a functional work system design as well as social interactions between humans and machines in cyber-physical systems. Such collaborative work systems consider the individual capabilities and potentials of humans and machines to combine them in a manner that assists the operator during his daily work routine. To be able to design such work systems, specific competences such as the ability of integrated process and product planning as well as systems and interface competence are required. Learning factories train students as well as professionals to gain such qualifications by providing a close-to-reality learning environment based on a didactical concept which covers all relevant methods for ergonomic work system design and a state-of-the-art infrastructure. Group-based, activity oriented scenarios enable the participants to put the learnings into their everyday work life. Thereby, learning factories have an indirect impact on the transfer of proven best practices to the industry.

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Metadaten
Name:Ranz, Fabian; Schuhmacher, Jan; Hummel, Vera
URL:https://www.highbeam.com/doc/1P3-4070057641.html
ISBN:978-1-5108-1368-7
Erschienen in:65th Annual Conference and Expo of the Institute of Industrial Engineers 2015 : Nashville, Tennessee, USA, 30 May - 2 June 2015. - Vol. 2
Publisher:Curran Associates Inc.
Place of publication:Red Hook, NY
Editor:Sila Cetinkaya
Document Type:Conference Proceeding
Language:English
Year of Publication:2015
Tag:collaborative work systems; competence development; ergonomics; learning factory; lifelong learning
Pagenumber:10
First Page:1419
Last Page:1428
Dewey Decimal Classification:620 Ingenieurwissenschaften und Maschinenbau
Open Access:Nein