Pregled bibliografske jedinice broj: 527350
Modeling the surface roughness during milling in off-line monitoring
Modeling the surface roughness during milling in off-line monitoring // Trends in the development of machinery and associated technology, TMT 2011 / Ekinović, Vivancos Calvet, Tacer (ur.).
Fojnica: Štamparija Fojnica, 2011. str. 821-824 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 527350 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Modeling the surface roughness during milling in off-line monitoring
Autori
Bajić, Dražen ; Jozić, Sonja ; Celent, Luka
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Trends in the development of machinery and associated technology, TMT 2011
/ Ekinović, Vivancos Calvet, Tacer - Fojnica : Štamparija Fojnica, 2011, 821-824
Skup
15th International Research/Expert Conference TMT 2011
Mjesto i datum
Prag, Češka Republika, 12.09.2011. - 18.09.2011
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
off-line process control; surface roughness; regression analysis; radial basis function neural network
Sažetak
Off-line process control improves process efficiency. This paper examines the influence of three cutting parameters on the surface roughness in face milling as part of the off-line process control. The experiments were carried out in order to define model for process planning. Cutting speed, the feed per tooth and the depth of cut were taken as influential factors. Two modeling methodologies, namely regression analysis and neural networks have been applied to experimentally determined data. Results obtained by the models have been compared. Both models have the relative prediction error below 10%. The research has shown that when training dataset is small neural networks modeling methodologies are comparable with regression analysis methodology and furthermore it can even offer better result, in this case average relative error of 6, 64%. Advantages of off-line process control which utilizes process models by using this two modeling methodologies were explained in theory.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
023-0692976-1742 - Istraživanje visokobrzinske obrade materijala (Bajić, Dražen, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split