Article: Reliability estimation of the sheet stamping process using support vector machines Journal: International Journal of Vehicle Design (IJVD) 2005 Vol.39 No.1/2 pp.110 - 124 Abstract: An important concern in sheet stamping is the risk of obtaining brittle final products that can be affected by fracture. Monte Carlo simulations presented herein show that this is governed by two main factors, namely static and dynamic friction coefficients. Whereas the latter correlates in a non-linear manner with minimum and maximum end thickness, the relationship of these design parameters to the former exhibits a bifurcation that is typical of highly non-linear phenomena, in which there is a sensitivity to small perturbations of the input values (chaos). In order to estimate the reliability of the process (i.e., the probability of obtaining brittle products due to low minimum and maximum thicknesses) with a reduced number of Monte Carlo runs, it is proposed to assimilate the problem to a pattern recognition task, due to the existence of two classes, namely robust and brittle. Among many pattern recognition algorithms that are useful to this end, use is made of support vector machines, as this incorporates the powerful tool of class margins that allow a drastic reduction of the number of simulations. Inderscience Publishers - linking academia, business and industry through research

Title: Reliability estimation of the sheet stamping process using support vector machines

Authors: Jorge E. Hurtado, Francisco Zarate, Eugenio Onate

Addresses: Universidad Nacional de Colombia, Manizales, Colombia. ' International Centre for Numerical Methods in Engineering, Technical University of Catalonia, Barcelona, Spain. ' International Centre for Numerical Methods in Engineering, Technical University of Catalonia, Barcelona, Spain

Abstract: An important concern in sheet stamping is the risk of obtaining brittle final products that can be affected by fracture. Monte Carlo simulations presented herein show that this is governed by two main factors, namely static and dynamic friction coefficients. Whereas the latter correlates in a non-linear manner with minimum and maximum end thickness, the relationship of these design parameters to the former exhibits a bifurcation that is typical of highly non-linear phenomena, in which there is a sensitivity to small perturbations of the input values (chaos). In order to estimate the reliability of the process (i.e., the probability of obtaining brittle products due to low minimum and maximum thicknesses) with a reduced number of Monte Carlo runs, it is proposed to assimilate the problem to a pattern recognition task, due to the existence of two classes, namely robust and brittle. Among many pattern recognition algorithms that are useful to this end, use is made of support vector machines, as this incorporates the powerful tool of class margins that allow a drastic reduction of the number of simulations.

Keywords: sheet metal stamping; pattern recognition; artificial intelligence; support vector machines; Monte Carlo simulation; metal forming; reliability estimation; fracture; brittle products; static friction coefficients; dynamic friction coefficients; thickness; quality control.

DOI: 10.1504/IJVD.2005.007223

International Journal of Vehicle Design, 2005 Vol.39 No.1/2, pp.110 - 124

Published online: 24 Jun 2005 *

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Title: Reliability estimation of the sheet stamping process using support vector machines

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