2013
DOI: 10.4028/www.scientific.net/msf.773-774.89
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A Method to Optimize Aluminum Alloy Door Impact Beam Stamping Process Using NSGA-II

Abstract: The process parameters of aluminium alloy hot stamping produce an importantly effect on production forming quality. In the case of a door impact beam inside the car doors, the fi-nite-element model of aluminium alloy hot stamping is set up. Based on the model, the forming quality is investigated under usual process condition. Using the Latin hypercube method, we sampled the data points from design space of process parameters. Data points are imported into finite-element model to calculate the forming quality i… Show more

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Cited by 2 publications
(2 citation statements)
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“…Many process parameters need to be considered in metal forming optimization, and their impacts on the forming quality and energy consumption are often contradictory. Then, the unavoidable contradiction would turn the optimization of metal forming processes into a multi-objective problem [95][96][97][98]. To reduce the influence of a stochastic property of process parameters on forming quality, some studies used the conjunction of multi-objective stochastic approach and response surface methodology to obtain optimal process parameters in hot stamping [99,100].…”
Section: Process Optimization For Energy Saving Of Metal Formingmentioning
confidence: 99%
“…Many process parameters need to be considered in metal forming optimization, and their impacts on the forming quality and energy consumption are often contradictory. Then, the unavoidable contradiction would turn the optimization of metal forming processes into a multi-objective problem [95][96][97][98]. To reduce the influence of a stochastic property of process parameters on forming quality, some studies used the conjunction of multi-objective stochastic approach and response surface methodology to obtain optimal process parameters in hot stamping [99,100].…”
Section: Process Optimization For Energy Saving Of Metal Formingmentioning
confidence: 99%
“…Kitayama et al used sequential approximate optimization with radial basis function network to optimize the parameter of blank holder force trajectory, with the aim of reducing the products' springback [17]. Zhou et al focused on numerical simulations, together with the combination of response surface methodology (RSM) and nondominated sorting genetic algorithm II (NSGA-II) to optimize aluminum alloy hot stamping [18]. In order to reduce the influence of the stochastic property of process parameters on forming quality, Xiao et al integrated multiobjective stochastic approaches, such as RSM, NSGA-II, and Monte Carlo simulations (MCSs), to obtain the optimal process parameters of aluminum hot stamping [19].…”
Section: Introductionmentioning
confidence: 99%