Optimality search and advanced regulation method of nc milling (CROSBI ID 591443)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Čuš, Franci ; Veža, Ivica ; Paulić, Matej ; Irgolić, Tomaž
engleski
Optimality search and advanced regulation method of nc milling
Owing to increasing demands and reduce of human impact on milling processes it is necessary that they are regulated and controlled by new regulation methods. In this article neural network method is described and represented on a concrete milling example. Neural network is developed and tested on measured cutting forces which occur in main coordinates. Neural network is formed to predict best cutting parameters and develop new one if necessary. With this method all logical reflection belongs to computer and trained neural network. Those methods reduce human impact and give us better results than standard optimization. During milling process neural network is trained for so long, that relative error is reduced to minimum. Relative error reduction to required values give us better final tolerance results after milling process and help us to increase milling process to higher intelligent level.
Milling; Neural Network; Regulation; Cutting Forces; Numerical Control
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Podaci o prilogu
943-946.
2012.
objavljeno
Podaci o matičnoj publikaciji
Annals of DAAAM for 2012. & Proceedings of the 23rd International DAAAM Symposium
Katalinić, Branko
Beč: DAAAM International Vienna
978-3-901509-91-9
Podaci o skupu
23rd International DAAAM Symposium Intelligent Manufacturing & Automation: Focus on Sustainability
predavanje
22.10.2012-28.10.2012
Zadar, Hrvatska