Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46218
Title: Lightweight optimization for additive manufacturing parts based on genetic algorithms, metamodels and finite element analysis
Authors: Paz, Rubén 
Monzón, Mario 
González, Begoña 
Winter, Gabriel 
Ortega, Fernando
UNESCO Clasification: 1206 Análisis numérico
120601 Construcción de algoritmos
Keywords: Lightweight optimization
Additive manufacturing
Genetic algorithms
Metamodels
Issue Date: 2015
Publisher: 1871-3033
Journal: Computational Methods in Applied Sciences 
Abstract: Additive manufacturing (AM) has become in a competitive method for short series production and high flexibility applications even for functional parts. Few constraints in the manufacturing process involve a great design freedom, allowing minimization of weight by using internal cellular and lattice structures, while minimal mechanical requirements are kept. Weight minimization implies a lower use of material and hence a reduction in manufacturing time, leading to a cost reduction. However, design optimization requires a greater effort in the design process, which also results in more costs. In order to reduce the design process, an optimization method based on genetic algorithms (GAs) and computer aided design/finite element method (CAD/FEM) simulations is proposed to optimize the cellular structure design and minimize the weight for AM parts. New optimization strategies based on GAs combined with surrogate models are evaluated and compared to reduce as much as possible the number of FEM simulations.
URI: http://hdl.handle.net/10553/46218
ISBN: 9783319204055
ISSN: 1871-3033
DOI: 10.1007/978-3-319-20406-2_5
Source: Computational Methods in Applied Sciences[ISSN 1871-3033],v. 39, p. 67-82
Appears in Collections:Actas de Congresos

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