Аутори:
1. Miloš Madić, Serbia
2. Miroslav Radovanović, Универзитет у Нишу, Машински факултет, Serbia
3. Dušan Petković, Универзитет у Нишу, Машински факултет, Serbia
4. Predrag Janković, Универзитет у Нишу, Машински факултет, Serbia
5. Miloš Milošević, Универзитет у Нишу, Машински факултет, Serbia

Апстракт:
In this paper, linear and quadratic regression models and artificial neural network model were developed to predict surface roughness for different values of cutting speed, laser power and assist gas pressure in CO2 laser cutting of mild steel. For the purpose of laser cutting experimentation Taguchi’s L25 orthogonal array was used arranging three factors at five levels. Surface roughness predicted values by both models were compared with the experimental values. The artificial neural network model was found to be capable of better predictions.

Кључне речи:
CO2 laser cutting,regression analysis,artificial neural networks,modeling

Тематска област:
Производне и рачунаром подржане технологије

Датум пријаве сажетка:
06.05.2015.

Конференцијa:
12th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2015)

Финални рад