60 resultados para british automotive industry
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Pós-graduação em Engenharia Mecânica - FEG
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Mecânica - FEG
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência e Tecnologia de Materiais - FC
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Aplicação de redes NeuroFuzzy ao processamento de peças automotivas por meio de injeção de polímeros
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The injection molding of automotive parts is a complex process due to the many non-linear and multivariable phenomena that occur simultaneously. Commercial software applications exist for modeling the parameters of polymer injection but can be prohibitively expensive. It is possible to identify these parameters analytically, but applying classical theories of transport phenomena requires accurate information about the injection machine, product geometry, and process parameters. However, neurofuzzy networks, which achieve a synergy by combining the learning capabilities of an artificial neural network with a fuzzy set's inference mechanism, have shown success in this field. The purpose of this paper was to use a multilayer perceptron artificial neural network and a radial basis function artificial neural network combined with fuzzy sets to produce an inference mechanism that could predict injection mold cycle times. The results confirmed neurofuzzy networks as an effective alternative to solving such problems.
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Arguments that lean manufacturing can positively relate with the operational performance of companies have been spreading the literature since the 1990s. However, there is a theoretical and empirical gap on this issue that needs further empirical evidence to validate or refute these arguments to the Brazilian reality. Hence, this research aims to, empirically, verify if the lean manufacturing positively influences the performance of the operations of companies in the Brazilian automotive industry, focusing on the segment of automotive parts and components. Methodologically, we carried out a survey of 75 companies in the mentioned sector. The data were analyzed using Structural Equation Modeling, a second-generation multivariate analysis. The main results of this research are: in fact, lean manufacturing positively affects the operational performance of the studied companies, validating the main hypothesis stated in this article, but this relation is just considered weak, although positive; all lean manufacturing practices analyzed were encountered in the reality, especially for the variable continuous improvement, with the highest average and the correlation between the adoption of Kanban and Just in Time; the operational performance construct has some practices/measures identified by the literature, which have not been validated by the studied sector, as innovation (new products) and quality.