A fuzzy-genetic system to predict the cutting force in microdrilling processes

This paper presents the modeling of thrust force in microdrilling processes of five commonly used alloys (titanium-based, tungsten-based, aluminum-based and invar). The process was carried out by peck drilling and the influence of five parameters (drill diameter, cutting speed, feed rate, one-step feed length and total drilling length) on the behavior of the thrust force was considered. A fuzzy system was used for describing these relationships and genetic algorithms were used for fitting the parameters of the model from the experimental data. Finally a comparison with a traditional cutting model obtained with a regression model was made showing both models a similar correlation values (R²), 0.84 for the regression model and 0.86 for the fuzzy-genetic system. However, the fuzzy model showed a better generalization capability (> 0.9) than the regression model, (very poor, near to 0).