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Dynamic value stream optimization for manual assembly in the learning factory for cyber-physical production systems

 
: Fink, K.; Sochor, R.; König, M.; Merkel, L.; Berg, J.; Reinhart, G.

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Volltext ()

Procedia manufacturing 45 (2020), S.78-83
ISSN: 2351-9789
Conference on Learning Factories (CLF) <10, 2020, Graz>
Englisch
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer IGCV ()

Abstract
In terms of globalization, producing companies are facing a high international competition. Therefore, many companies have to enable their production systems and their employees for mass customization. Especially in manual assembly, rising product variance and complexity can lead to a lower overall equipment effectiveness (OEE) and higher error rates. In order to master rising product variance and complexity, digital assistance systems can support the production manager and the assembly worker by providing, transmitting and receiving product information ongoing and in real-time. This paper presents a process model for selecting digital assistance systems and developing an agile work organization in the learning factory for cyber-physical production systems (LVP). Based on an assembly scenario of remote-controlled cars, participants are supported by a digital dashboard, which visualizes their net production time, open capacity and level of synchronization in real time. First observations in the LVP show that participants are able to analyze their current value stream, detect the bottleneck assembly station and optimize their value stream by shifting participants to assembly stations with a higher net-production time or shifting assembly tasks to other assembly stations with a lower net-production time independently.

: http://publica.fraunhofer.de/dokumente/N-596060.html