Author(s):
1. Marin Gostimirović, Faculty of Technical Sciences, Department for Production Engineering, Serbia
2. Dragan Rodić, Faculty of Technical Sciences, Department for Production Engineering, Serbia
3. Pavel Kovač, Faculty of Technical Sciences, Department for Production Engineering, Serbia
4. Vladimir Pucovsky, Faculty of Technical Sciences, Department for Production Engineering, Serbia
5. Borislav Savković, Faculty of Technical Sciences, Department for Production Engineering, Serbia

Abstract:
This paper reports the development of two intelligent models for the electric discharge machining (EDM) process using adaptive-neuro-fuzzy-inference system (ANFIS) and genetic programming (GP). Experiments were conducted by varying the pulse duration and discharge current and the corresponding values of surface roughness (Ra) were measured. The values of surface roughness predicted by these models are then compared. Both models show good agreement with experimental results. The results indicate that the genetic programming technique gives slightly smaller deviation of the measured values of model than neuro-fuzzy model.

Key words:
neuro-fuzzy systems,genetic programming,surface roughness

Date of abstract submission:
14.02.2013.

Conference:
DEMI 2013

Applied paper from author