Naslov
Modelling of kerf width in plasma jet metal cutting process using ANN approach

Autori
Peko, Ivan ; Nedić, Bogdan ; Đorđević, Aleksandar ; Veža, Ivica

Izvornik
Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku (1330-3651) 25 (2018), 2; 401-406

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
artificial neural networks ; kerf width ; modeling ; plasma jet metal cutting

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.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

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