%0 Journal Article
	%A H.Mohammadi Majd and  M.Jalali Azizpour and  A.V. Hoseini
	%D 2011
	%J International Journal of Mechanical and Mechatronics Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 50, 2011
	%T Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process
	%U https://publications.waset.org/pdf/13112
	%V 50
	%X In this paper back-propagation artificial neural
network (BPANN) is employed to predict the limiting drawing ratio
(LDR) of the deep drawing process. To prepare a training set for
BPANN, some finite element simulations were carried out. die and
punch radius, die arc radius, friction coefficient, thickness, yield
strength of sheet and strain hardening exponent were used as the
input data and the LDR as the specified output used in the training of
neural network. As a result of the specified parameters, the program
will be able to estimate the LDR for any new given condition.
Comparing FEM and BPANN results, an acceptable correlation was
	%P 356 - 359