Predicting surface roughness of AISI 4140 steel in hard turning process through artificial neural network, fuzzy logic and regression models
Küçük Resim Yok
Tarih
2011
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, the average surface roughness values obtained when turning AISI 4140 grade tempered steel with a hardness of 51 HRC, were modeled using fuzzy logic, artificial neural networks (ANN) and multi-regression equations. Input variables consisted of cutting speed (V), feed rate (f) and depth of cut (a) while output variable was surface roughness (Ra). Fuzzy logic and ANN models were developed using Matlab Toolbox. Variance analysis was conducted using MINITAB. The predicted values of mean squared errors (MSE) were employed to compare the three models. Results showed that the optimum predictive model is the fuzzy logic model. With small errors (e.g MSE = 0.0173166), the model was considered sufficiently accurate. © 2011 Academic Journals.
Açıklama
Anahtar Kelimeler
Artificial neural network, Fuzzy logic model, Hard turning, Multi regression model, Surface roughness
Kaynak
Scientific Research and Essays
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
6
Sayı
13
