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Pregled bibliografske jedinice broj: 651866

Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization


Šimunović, Katica; Šimunović, Goran; Šarić, Tomislav
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

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Šimunović, Katica; Šimunović, Goran; Šarić, Tomislav
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)
Šimunović, K., Šimunović, G. & Šarić, T. (2013) Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization. Measurement science review, 13 (5), 265-272 doi:10.2478/msr-2013-0039.
@article{article, author = {\v{S}imunovi\'{c}, Katica and \v{S}imunovi\'{c}, Goran and \v{S}ari\'{c}, Tomislav}, year = {2013}, pages = {265-272}, DOI = {10.2478/msr-2013-0039}, keywords = {Surface roughness, face milling, aluminium alloy, experimental design, regression model}, journal = {Measurement science review}, doi = {10.2478/msr-2013-0039}, volume = {13}, number = {5}, issn = {1335-8871}, title = {Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization}, keyword = {Surface roughness, face milling, aluminium alloy, experimental design, regression model} }
@article{article, author = {\v{S}imunovi\'{c}, Katica and \v{S}imunovi\'{c}, Goran and \v{S}ari\'{c}, Tomislav}, year = {2013}, pages = {265-272}, DOI = {10.2478/msr-2013-0039}, keywords = {Surface roughness, face milling, aluminium alloy, experimental design, regression model}, journal = {Measurement science review}, doi = {10.2478/msr-2013-0039}, volume = {13}, number = {5}, issn = {1335-8871}, title = {Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization}, keyword = {Surface roughness, face milling, aluminium alloy, experimental design, regression model} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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