Selection of optimal machining conditions for the composite materials by using Taguchi and GONNs
Küçük Resim Yok
Tarih
2014
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier B.V.
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
Anahtar Kelimeler
Genetic algorithm, GFRP, GONNs, Milling, Neural network
Kaynak
Measurement: Journal of the International Measurement Confederation
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
48
Sayı
1
