Tool wear prediction in turning of Inconel 718 caircraft engine components is carried out through a supervised neural network approach on the basis of experimental data obtained during machining test performed in the production shop floor by taking into account production shift requirements. The neural network tool wear prediction accuracy is shown to be 92% for the whole range of considered process parameters as early as 270 s of cutting time.
Neural Network Tool Wear Prediction in Turning of Inconel 718 / Teti, Roberto; D'Addona, DORIANA MARILENA; Segreto, Tiziana; A., Simeone; G., De Chiara; L., Gabriele; R., Marrone. - STAMPA. - 6:(2008), pp. 199-203.
Neural Network Tool Wear Prediction in Turning of Inconel 718
TETI, ROBERTO;D'ADDONA, DORIANA MARILENA;SEGRETO, Tiziana;
2008
Abstract
Tool wear prediction in turning of Inconel 718 caircraft engine components is carried out through a supervised neural network approach on the basis of experimental data obtained during machining test performed in the production shop floor by taking into account production shift requirements. The neural network tool wear prediction accuracy is shown to be 92% for the whole range of considered process parameters as early as 270 s of cutting time.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
