Napredna pretraga

Pregled bibliografske jedinice broj: 305511

Modeling of the influence of cutting parameters on the surface roughness, tool wear and the cutting force in face milling in off-line process control


Bajić, Dražen; Celent, Luka; Jozić, Sonja
Modeling of the influence of cutting parameters on the surface roughness, tool wear and the cutting force in face milling in off-line process control // STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 58 (2012), 11; 673-682 doi:10.5545/sv-jme.2012.456 (međunarodna recenzija, članak, znanstveni)


Naslov
Modeling of the influence of cutting parameters on the surface roughness, tool wear and the cutting force in face milling in off-line process control

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

Izvornik
STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING (0039-2480) 58 (2012), 11; 673-682

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Off-line process control; Surface roughness; Cutting force; Tool wear; 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, tool wear and the cutting force components in face milling as part of the off-line process control. The experiments were carried out in order to define a model for process planning. Cutting speed, feed per tooth and 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 a relative prediction error below 10%. The research has shown that when the training dataset is small neural network modeling methodologies are comparable with regression analysis methodology and furthermore can even offer better results, in this case an average relative error of 3, 35%. Advantages of off-line process control which utilizes process models by using these two modeling methodologies are 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

Časopis indeksira:


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


Uključenost u ostale bibliografske baze podataka:


  • SCI-Expanded, Advanced Polymer Abstracts, Aluminium Industry Abstracts,


Citati