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Examinantion and Modeling of the Influence of Cutting Parameters on the Surface Roughness in Face Milling


Bajić, Dražen; Gjeldum, Nikola; Veža, Ivica
Examinantion and Modeling of the Influence of Cutting Parameters on the Surface Roughness in Face Milling // Eighth International Conference on Advanced Manufacturing Systems Proceedings / Kuljanić, Elso (ur.).
Udine: International Centre for Mechanical Sciences, 2008. str. 123-133 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Examinantion and Modeling of the Influence of Cutting Parameters on the Surface Roughness in Face Milling
(Cutting Parameters on the Surface Roughness in Face Milling)

Autori
Bajić, Dražen ; Gjeldum, Nikola ; Veža, Ivica

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Eighth International Conference on Advanced Manufacturing Systems Proceedings / Kuljanić, Elso - Udine : International Centre for Mechanical Sciences, 2008, 123-133

ISBN
88-85137-22-9

Skup
AMST'08 Advanced Manufacturing Systems and Technology

Mjesto i datum
Udine, Italija, 12-13.06.2008

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Face milling; Surface roughness; Regression; Neutral networks

Sažetak
Surface roughness, as indicator of surface quality, is one of the most specified customer requirements in machining of parts. This study examines the influence of three cutting parameters on the surface roughness in face milling. The cutting speed, the feed rate and the depth of cut have been taken as influential factors. Two modelling methodology, namely regression analysis and neural networks, have been applied to experimentally determined data. Also, for both methodologies the ability of interpolation and extrapolation has been tested. Results obtained by neural network models have been compared to those obtained by regression models. Both methodologies give nearly similar results when interpolation is observed. However, regarding extrapolation neural network models give better results.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekt / tema
023-0231926-2194 - Tehnološko-organizacijsko optimiranje kompetencijske stanice (Ivica Veža, )
023-0692976-1742 - Istraživanje visokobrzinske obrade materijala (Dražen Bajić, )

Ustanove
Fakultet elektrotehnike, strojarstva i brodogradnje, Split