Pregled bibliografske jedinice broj: 778729
Predictive models for surface roughness of face milled S235JRG2 structural steel
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)
CROSBI ID: 778729 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
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, 24.09.2015. - 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
Projekti:
152-1521781-2235 - Razvoj ERP sustava za digitalno poduzeće (Šarić, Tomislav, MZOS ) ( CroRIS)
Ustanove:
Strojarski fakultet, Slavonski Brod
Profili:
Roberto Lujić
(autor)
Sara Havrlišan
(autor)
Katica Šimunović
(autor)
Goran Šimunović
(autor)
Tomislav Šarić
(autor)