Optimisation of machining parameters of train wheel for shrink-fit application by considering surface roughness and chip morphology parameters
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier - Division Reed Elsevier India Pvt Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The train wheel is one of the elements most exposed to static and dynamic loads during the transport. For this reason, it is of great importance for the safety of rail transportation that the wheel-axle assembly is carried out securely through the shrink-fit method. The surface roughness of the inner diameter of the wheel must be within 0.8-3.2 mu m in order to provide the optimum shrink-fit. In this study, different depth-of-cut, feed rate and cutting speed parameters were considered in the turning process of ER8 class train wheel, and optimum machinability parameters were determined. In the experimental study, the Taguchi experimental design method, regression analysis and variance analysis (ANOVA) method were used. Experimental results were examined visually by using chip photographs and SEM images. According to the ANOVA results, it was determined that the most effective parameter is the feed rate with 93.78% on surface roughness in the turning of the train wheel. The SEM images derived from chips proved that the feed rate has strong correlation with surface roughness. Optimum machining parameters were determined as 1.5 mm depth of cut, 0.1 mm/rev feed rate and 250 rpm cutting speed. (c) 2020 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Açıklama
Anahtar Kelimeler
Train wheel, Taguchi method, Surface roughness, ANOVA, Regression analysis
Kaynak
Engineering Science and Technology-An International Journal-Jestech
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
23
Sayı
5