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Approach to Generate Optimized Assembly Sequences from Sensor Data

 
: Kärcher, Susann; Bauernhansl, Thomas

:
Volltext urn:nbn:de:0011-n-5525379 (1.0 MByte PDF)
MD5 Fingerprint: e81a10efb99cf64af96e622b3e924d9c
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Erstellt am: 30.7.2019


Procedia CIRP 81 (2019), S.276-281
ISSN: 2212-8271
Conference on Manufacturing Systems (CMS) <52, 2019, Ljubljana>
Englisch
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
Montage; Analyse; manual; manuelle Montage; Montageprozess; Optimierung; Sensor

Abstract
Manual assembly processes are often plagued with a lack of transparency while holding great potential for optimization. As preparing instructions takes a lot of time, assembly processes are often poorly documented, particularly for small volumes. This paper presents a general approach to automatically generate optimized process step sequences in manual assemblies from sensor data. The idea is to analyze the data and compare different assembly processes captured by the analysis. From this, a best practice can be derived and standard times can be defined for the individual process steps.

: http://publica.fraunhofer.de/dokumente/N-552537.html