Selection of optimal machining conditions for the composite materials by using Taguchi and GONNs
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Dosyalar
Tarih
2014
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Sci Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Milling has been widely used in industry for machining parts to their final dimensions without requiring additional operations. Extensive experimental work is necessary to determine the optimal cutting conditions of glass-fiber reinforced polymer composite (GFRP) materials to achieve the desired surface quality. In this study, a series of machining operations were done for data collection by varying the flute number, feed rate, depth of cut and cutting speed. The relationship between the cutting parameters of end milling operations and the surface roughness of the machined surface was studied. For the analysis of the data and selection of the optimal cutting parameters the Taguchi method and genetically optimized neural network systems (GONNs) were used. Published by Elsevier Ltd.
Açıklama
ERKAN, Omer/0000-0002-9428-4299
WOS: 000329207400034
WOS: 000329207400034
Anahtar Kelimeler
GFRP, Milling, Neural network, Genetic algorithm, GONNs
Kaynak
Measurement
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
48
