Pregled bibliografske jedinice broj: 651866
Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization
Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization // Measurement science review, 13 (2013), 5; 265-272 doi:10.2478/msr-2013-0039 (međunarodna recenzija, članak, znanstveni)
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Naslov
Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization
Autori
Šimunović, Katica ; Šimunović, Goran ; Šarić, Tomislav
Izvornik
Measurement science review (1335-8871) 13
(2013), 5;
265-272
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Surface roughness; face milling; aluminium alloy; experimental design; regression model
Sažetak
The surface roughness is a very significant indicator of surface quality. It represents an essential exploitation requirement a nd influences technological time and costs, i.e. productivity. For that reason, the main objective of this paper is to analyse the influence of face milling cutting parameters (number of revolution, feed rate and depth of cut) on the surface roughness of aluminium alloy. Hence, a statistical (regression) model has been developed to predict the surface roughness by using the methodology of experimental design. Central composite design is chosen for fitting response surface. Also, numerical optimization considering two goals simultaneously (minimum propagation of error and minimum roughness) was performed throughout the experimental region. In this way, the settings of cutting parameters causing the minimum variabilit y in response were determine d for the estimated variations of the significant regression factors.
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
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus