VGCIVaseline Glass Collectors Inc
Copyright 1988-2018, All rights reserved.
References in periodicals archive ?
In this paper, cutting force was measured during the turning process of VGCI. The effects of cutting parameters, such as hardness of VGCI, speed and feed rate, were evaluated.
In this study, a technique was proposed to predict cutting force of austempered vermicular graphite cast irons (VGCI) by using neural network.
Table 1 Chemical composition of experimental VGCI (wt %) C Si Mn P S Cr Cu Mg Sn Sn 3.74 2.30 0.37 0.0027 0.014 0.0044 0.056 0.013 0.14 0.14 Table 2 Accuracy of predictions of the neural network model RMSE [R.sup.2] Training Test Training Normalized 1.16E-07 0.0163 0.9999 Real 9.12E-05 12.8452 0.9999 MAE MPE Test Training Test Training Test Normalized 0.9962 8.25E-08 0.0046 9.73E-06 0.5530 Real 0.9962 6.50E-05 3.6000 9.73E-06 0.5530