E,Experimental ınvestigation of cutting speed on the surface roughness for cnc machine
Yükleniyor...
Dosyalar
Tarih
03-05 May, 2018, 3-5 Mayıs 2018
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IETS'18 International Engineering and Technology Symposium
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
CNC (Computer Numerical Control) machines have high precision and fast processing
capabilities and are the result of the optimization of conventional machines. Because of their
superiority, they now have a widespread use in many different industrial manufacturing sectors.
The most common usage areas of CNC machines are the machining sector. The method of
processing during machining depends on the type of cutter and the material being processed.
During machining, surface roughness is formed on the machined surfaces due to the physical,
chemical and thermal factors, mechanical movements between cutting and cutting. In other
words, the surface roughness is irregular deviations below and above the nominal surface line.
Minimizing surface roughness during machining is an important issue for the industrial sector.
The quality of the processed surfaces plays an important role on the machining performance. A
quality machined surface improves fatigue strength, corrosion resistance and friction life
significantly. Surface roughness also affects the various functional properties of parts such as
contact, abrasion, heat conduction, oil flame retention and dispersibility, coating or resistance
life, which cause surface friction. For this reason, the desired surface finish is generally
determined and appropriate procedures are selected to achieve the required quality ....
Açıklama
Anahtar Kelimeler
CNC Machine, surface roughness
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Nalbant, m., gökkaya, h., toktaş, i., & sur, g. (2009). the experimental investigation of the effects of uncoated, pvd-and cvd-coated cemented carbide inserts and cutting parameters on surface roughness in cnc turning and its prediction using artificial neural networks. robotics and computer-ıntegrated manufacturing, 25(1), 211-223.
