udimet 720
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2016 ◽  
pp. 415-426 ◽  
Author(s):  
Marie-Agathe Charpagne ◽  
Marie-Agathe Charpagne ◽  
Thomas Billot ◽  
Jean-Michel Franchet ◽  
Nathalie Bozzolo


Procedia CIRP ◽  
2016 ◽  
Vol 45 ◽  
pp. 283-286 ◽  
Author(s):  
R. Hood ◽  
J. Morris ◽  
S.L. Soo


2013 ◽  
Vol 581 ◽  
pp. 366-371 ◽  
Author(s):  
Marek Vrabel' ◽  
Ildikó Maňková ◽  
Jozef Beňo

Article deals with design of artificial neural network (ANN) for prediction of the surface roughness as one of the important indicators of machined surface quality. Back propagation neural network was trained and tested for prediction of the machined surface roughness. Cutting conditions, selected monitoring indices and tool wear parameter were given as inputs to the ANN. Test sample was nickel based super alloy Udimet 720, which is used as material for highly stressed jet engine components. Experimental data collected from tests were used as input into ANN to identify the sensitivity among cutting conditions, monitoring indices and progressive tool wear and machined surface roughness.



2012 ◽  
Vol 42 ◽  
pp. 295-300 ◽  
Author(s):  
M.T. Antar ◽  
S.L. Soo ◽  
D.K. Aspinwall ◽  
C. Sage ◽  
M. Cuttell ◽  
...  


2012 ◽  
Vol 48 ◽  
pp. 693-700 ◽  
Author(s):  
Marek Vrabeľ ◽  
Ildiko Mankova ◽  
Jozef Beno ◽  
Jaroslav Tuharský


2010 ◽  
Vol 27 (4) ◽  
pp. 295-300
Author(s):  
Kartik Prasad ◽  
Rajdeep Sarkar ◽  
P. Ghosal ◽  
G. Appa Rao ◽  
Vikas Kumar


2010 ◽  
Vol 32 (5) ◽  
pp. 824-829 ◽  
Author(s):  
T. Billot ◽  
P. Villechaise ◽  
M. Jouiad ◽  
J. Mendez


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