AISI 8740 çeliğinin frezelenmesinde kesme gücü, özgül kesme enerjisi ve yüzey pürüzlülüğü karakteristiklerinin belirlenmesi
Öz
Anahtar Kelimeler
Kaynakça
- Kuram E., Nose radius and cutting speed effects during milling of AISI 304 material, Mater. Manuf. Process., 32(2), 185-192, 2017.
- Deng Z., Zhang H., Fu Y., Wan L., Liu W., Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption, J. Clean. Prod., 166, 1407-1414, 2017.
- Zhang H., Deng Z., Fu Y., Lv L., Yan C., A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions, J. Clean. Prod., 148, 174-184, 2017.
- Liu N., Wang S.B., Zhang Y.F., Lu W.F., A novel approach to predicting surface roughness based on specific cutting energy consumption when slot milling Al-7075, Int. J. Mech. Sci., 118, 13-20, 2016.
- Dhar N.R., Kamruzzaman M., Effects of cryogenic cooling on temperature, tool wear, surface roughness and dimensional deviation in turning AISI-8740 steel by coated carbide, Proc. of the 1st Int. Conf. & 7th AUN/SEED-Net Fieldwise Seminar on Manuf. and Mater. Process., Kuala Lumpur, 36-41, 2006.
- Liu G., Huang C., Zhu H., Liu Z., Liu, Y., Li, C., The modified surface properties and fatigue life of Incoloy A286 face-milled at different cutting parameters, Mater. Sci. Eng. A, 704, 1-9, 2017.
- Urbikain G., de Lacalle L.N.L., Modelling of surface roughness in inclined milling operations with circle segment end mills, Simul. Model. Pract. Theory, 84, 161-176, 2018.
- Yao C.F., Wu D.X., Ma L.F., Tan L., Zhou Z.,Zhang J.Y., Surface integrity evolution and fatigue evaluation after milling mode, shot-peening and polishing mode for TB6 titanium alloy, Appl. Surf. Sci., 387, 1257–1264, 2016.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Ferah Sucularlı
Bu kişi benim
0000-0002-5839-2356
Türkiye
Asim Genç
0000-0002-1900-1009
Türkiye
Yayımlanma Tarihi
28 Şubat 2022
Gönderilme Tarihi
5 Haziran 2021
Kabul Tarihi
26 Kasım 2021
Yayımlandığı Sayı
Yıl 2022 Cilt: 37 Sayı: 4
Cited By
Prediction of cutting performance in slot milling process of AISI 316 considering energy efficiency using experimental and machine learning methods
Multidiscipline Modeling in Materials and Structures
https://doi.org/10.1108/MMMS-12-2024-0371