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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 (CROSBI ID 133604)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

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 // Strojniški vestnik, 58 (2012), 11; 673-682. doi: 10.5545/sv-jme.2012.456

Podaci o odgovornosti

Bajić, Dražen ; Celent, Luka ; Jozić, Sonja

engleski

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

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.

Off-line process control; Surface roughness; Cutting force; Tool wear; Regression Analysis; Radial basis function neural network

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Podaci o izdanju

58 (11)

2012.

673-682

objavljeno

0039-2480

10.5545/sv-jme.2012.456

Povezanost rada

Strojarstvo

Poveznice
Indeksiranost