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http://hdl.handle.net/11452/22642
Başlık: | Surface roughness model in machining hardened steel with cubic boron nitride cutting tool |
Yazarlar: | Şahin, Yusuf Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu/Makine Programı. 0000-0002-9129-8935 Motorcu, Ali Rıza G-5458-2017 6507857056 |
Anahtar kelimeler: | Turning CBN tools Surface roughness Response surface method Regression Prediction Prediction Wear Machinability Parameters Vibrations Design Cubic boron nitride Cutting tools Machining Surface roughness Cutting speed Feed rate Response surface method Steel Materials science Metallurgy & metallurgical engineering |
Yayın Tarihi: | 2008 |
Yayıncı: | Elsevier Science |
Atıf: | Şahin, Y. ve Motorcu A. R. (2008). ''Surface roughness model in machining hardened steel with cubic boron nitride cutting tool''. International Journal of Refractory Metals & Hard Materials, 26(2), 84-90. |
Özet: | The surface roughness model was developed in terms of main cutting parameters such as cutting speed, feed rate and depth of cut, using response surface methodology. Machining tests were carried out in turning AISI 1050 hardened steels by cubic boron nitride (CBN) cutting tools under different conditions. The model predicting equations for surface roughness of R-a, R-z, and R-max were developed using an experimental data when machining steels. The results indicate that the feed rate was found out to be dominant factor on the surface roughness, but it decreased with decreasing cutting speed, feed rate, depth of cut for these tools. In addition, average surface finish of Ra value produced by CBN cutting tool was about 0.823 mu m when machining hardened steels. However, the Ra value decreased about 0.55 mu m in terms of trial conditions. Moreover, a good agreement between the predicted and experimental surface roughness was observed within reasonable limit. |
URI: | https://www.sciencedirect.com/science/article/pii/S0263436807000261 https://doi.org/10.1016/j.ijrmhm.2007.02.005 http://hdl.handle.net/11452/22642 |
ISSN: | 0263-4368 |
Koleksiyonlarda Görünür: | Scopus Web of Science |
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