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Resource efficiency optimization of manufacturing processes using evolutionary computation: A turning case

 
: Kübler, Frank; Böhner, Johannes; Steinhilper, Rolf

:
Volltext urn:nbn:de:0011-n-3495273 (864 KByte PDF)
MD5 Fingerprint: 0312e87e1a520cb5bf8d395fd504487f
(CC) by-nd
Erstellt am: 21.7.2015


Procedia CIRP 29 (2015), S.822-827
ISSN: 2212-8271
Conference on Life Cycle Engineering <22, 2015, Sydney>
Englisch
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
Genetischer Algorithmus; genetic algorithm; Effizienzsteigerung; Algorithmus

Abstract
Most resource efficiency optimization measures being discussed in resent publications focus on component downsizing and adaptive control of components regarding the standard ISO 14955. Optimization of discrete manufacturing process parameter is a further approach to reduce resource consumption during operation. This paper presents a meta heuristic genetic algorithm approach which has been used to determine a pareto front of feasible machining parameter. The pareto front is used to select optimal solutions for the resource consumption integrated multi-dimensional optimization task. The results are presented for a turning process with respect to resource consumption, machining time and machining cost under product quality constrains and machine performance limits.

: http://publica.fraunhofer.de/dokumente/N-349527.html