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Pregled bibliografske jedinice broj: 778729

Predictive models for surface roughness of face milled S235JRG2 structural steel


Šimunović, Goran; Šarić, Tomislav; Šimunović, Katica; Lujić, Roberto; Svalina, Neven; Havrlišan, Sara
Predictive models for surface roughness of face milled S235JRG2 structural steel // ZBORNIK RADOVA/CONFERENCE PROCEEDINGS STROJARSKE TEHNOLOGIJE I KONSTRUKCIJSKI MATERIJALI/MECHANICAL TECHNOLOGIES AND STRUCTURAL MATERIALS / Jozić, Sonja ; Lela, Branimir (ur.).
Split: Hrvatsko društvo za strojarske tehnologije, 2015. str. 145-154 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Predictive models for surface roughness of face milled S235JRG2 structural steel

Autori
Šimunović, Goran ; Šarić, Tomislav ; Šimunović, Katica ; Lujić, Roberto ; Svalina, Neven ; Havrlišan, Sara

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

Izvornik
ZBORNIK RADOVA/CONFERENCE PROCEEDINGS STROJARSKE TEHNOLOGIJE I KONSTRUKCIJSKI MATERIJALI/MECHANICAL TECHNOLOGIES AND STRUCTURAL MATERIALS / Jozić, Sonja ; Lela, Branimir - Split : Hrvatsko društvo za strojarske tehnologije, 2015, 145-154

Skup
5th International Conference on Mechanical Technologies and Structural Materials 2015

Mjesto i datum
Split, Hrvatska, 24-25.09.2015

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Central composite design; Regression model; Surface roughness; S235JRG2 steel

Sažetak
In addition to the depth of cut, spindle speed and feed rate, the paper investigates the influence of the fourth input variable – way of cooling/lubricating (dry cutting conditions, cooling/lubricating through the tool and flood cooling/lubricating) on the surface roughness of face milled S235JRG2 structural steel. The results of the performed face-centered central composite design are shown in the form of regression models obtained from experimental data, the main aim being to represent the relationship between the roughness and input variables. In the obtained quadratic regression model, significant factors are the spindle speed, feed rate and cooling/lubricating, the interaction of linear spindle speed with cooling/lubricating and the quadratic terms of depth of cut and feed rate. Likewise, at each level of the cooling/lubricating factor, a quadratic model in the three factors is fitted.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekt / tema
152-1521781-2235 - Razvoj ERP sustava za digitalno poduzeće (Tomislav Šarić, )

Ustanove
Strojarski fakultet, Slavonski Brod