Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/74353

TítuloMulti-objective optimization of plastics thermoforming
Autor(es)Gaspar-Cunha, A.
Costa, Paulo
Galuppo, Wagner de Campos
Nóbrega, J. M.
Duarte, F. M.
Costa, Lino
Palavras-chavePlastics thermoforming
Sheet thickness distribution
Evolutionary algorithms
Multiobjective optimization
Data26-Jul-2021
EditoraMultidisciplinary Digital Publishing Institute (MDPI)
RevistaMathematics
CitaçãoGaspar-Cunha, A.; Costa, P.; Galuppo, W.d.C.; Nóbrega, J.M.; Duarte, F.; Costa, L. Multi-Objective Optimization of Plastics Thermoforming. Mathematics 2021, 9, 1760. https://doi.org/10.3390/math9151760
Resumo(s)The practical application of a multi-objective optimization strategy based on evolutionary algorithms was proposed to optimize the plastics thermoforming process. For that purpose, in this work, differently from the other works proposed in the literature, the shaping step was considered individually with the aim of optimizing the thickness distribution of the final part originated from sheets characterized by different thickness profiles, such as constant thickness, spline thickness variation in one direction and concentric thickness variation in two directions, while maintaining the temperature constant. As far we know, this is the first work where such a type of approach is proposed. A multi-objective optimization strategy based on Evolutionary Algorithms was applied to the determination of the final part thickness distribution with the aim of demonstrating the validity of the methodology proposed. The results obtained considering three different theoretical initial sheet shapes indicate clearly that the methodology proposed is valid, as it provides solutions with physical meaning and with great potential to be applied in real practice. The different thickness profiles obtained for the optimal Pareto solutions show, in all cases, that that the different profiles along the front are related to the objectives considered. Also, there is a clear improvement in the successive generations of the evolutionary algorithm.
TipoArtigo
URIhttps://hdl.handle.net/1822/74353
DOI10.3390/math9151760
e-ISSN2227-7390
Versão da editorahttps://www.mdpi.com/2227-7390/9/15/1760
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:IPC - Artigos em revistas científicas internacionais com arbitragem

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