Tehnički vjesnik, Vol. 25 No. 2, 2018.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20161024093323
Modelling of Kerf Width in Plasma Jet Metal Cutting Process using ANN Approach
Ivan Peko
orcid.org/0000-0001-5048-9842
; Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Ruđera Boškovića 32, 21000 Split, Croatia
Bogdan Nedić
; Faculty of Engineering, University of Kragujevac, Sestre Janjić 6, 34000 Kragujevac, Serbia
Aleksandar Đorđević
orcid.org/0000-0003-2856-6578
; Faculty of Engineering, University of Kragujevac, Sestre Janjić 6, 34000 Kragujevac, Serbia
Ivica Veža
; Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Ruđera Boškovića 32, 21000 Split, Croatia
Sažetak
In this paper Artificial Neural Network (ANN) model was developed for prediction of kerf width in plasma jet metal cutting process. Process parameters whose influence was analyzed are cutting height, cutting speed and arc current. An L18 (21x37) Taguchi orthogonal array experiment was conducted on aluminium sheet of 3 mm thickness. Using the experimental data a feed – forward backpropagation artificial neural network model was developed. After the prediction accuracy of the developed model was verified, the model was used to generate plots that show influence of process parameters and their interactions on analzyed kerf width and to get conlusions about process parameters values that lead to minimal kerf width.
Ključne riječi
artificial neural networks; kerf width; modelling; plasma jet metal cutting
Hrčak ID:
199136
URI
Datum izdavanja:
21.4.2018.
Posjeta: 2.429 *