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Pregled bibliografske jedinice broj: 527350

Modeling the surface roughness during milling in off-line monitoring


Bajić, Dražen; Jozić, Sonja; Celent, Luka
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)


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, 12-18.09.2011

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


Projekt / tema
023-0692976-1742 - Istraživanje visokobrzinske obrade materijala (Dražen Bajić, )

Ustanove
Fakultet elektrotehnike, strojarstva i brodogradnje, Split