Advances in Materials Processing Technologies: Mesic V by Juan José Aguilar Martin, José Antonio Yagüe Fabra

By Juan José Aguilar Martin, José Antonio Yagüe Fabra

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The artificial neuronal networks were based on a multilayered perceptron with trainLm training using tansig transference. In order to obtain optimum models, several neuronal networks were configured according to the number of hidden layers (2, 4, 6, 8, 10), and the number of neurons per layer (3, 6, 9, 12), with adjusted R2-adjusted above 90%. The mean relative error predictions for the selected neuronal networks are shown in Table 2. The analysis was applied to the signals of each individual sensor (dynamometer, accelerometer, and piezotron), and to the different combinations of sensors.

International Journal of Machine Tools & Manufacture (2011) vol 51, 740-744. [9] H. Hocheng, C. C, Tsao. Comprehensive analysis of delamination in drilling of composite materials with various drills bits. Journal of Material Processing Technology (2004), vol 140, 335339. [10] A. Faraz, et al. Cutting Edge Rounding: An Innovate Tool Wear Criterion in Drilling CFRP Composite Laminates, International Journal of Machine Tools & Manufacture (2009), vol 49, 11851196. Materials Science Forum Vol. 41 Contribution of Surface Finish Monitoring Signals in CNC Taper Turning E.

First of them is based on the analysis of the diameter deviation. Second procedure is based on the damaged area. Experimental Dry drilling tests of CFRC plates were performed in a Kondia (Five-400 model) High Speed Machining Center (HSMC), equipped with a Heidenhain iTNC530 numerical control. 1 mm/rev have been selected as cutting parameters starting from the data recorded in [2-6]. Fifty holes were dry machined on each pair of conditions (S, f), employing two helical edges uncoated carbide twist drills (WC-Co), with standard geometry (helix angle=28o; End Point Angle=118o), Fig.

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