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1 Prace Naukowe Instytutu Technologii Maszyn i Automatyzacji Politechniki Wrocławskiej. Konferencje

1 2003

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Modelling of end milling process by generalized regression networks

Župerl U., Čuš F., Balič J.

Prace Naukowe Instytutu Technologii Maszyn i Automatyzacji Politechniki Wrocławskiej. Konferencje

2003

Vol. 84, nr 41

337-344

Supervised neural network algorithms are developed for use as a direct modelling method, to predict forces for ball-end milling operation. The training of the networks is performed with experimental machining data This paper uses the regression neural networks approach to evolve an efficient model for estimation of cutting forces, based on a set of input cutting conditions. The predictive capability of using analytical and neural network approaches are compared using statistics, which showed that neural network predictions for three cutting force components were for 4% closer to the experimental measurements, compared to 11% using analytical method. Exhaustive experimentation is conduced to develop the model and to validate it. The milling experiments prove that this model can predict accurately the cutting forces in three Cartesian directions.