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Decision Support Systems Intelligent to Predict and Optimize the Assembly Time for New Product Design Using a Fuzzy-Evolutionary Multimodal Approach
Pedro Pérez Villanueva
Elias Gabriel Carrum Siller
Acceso Abierto
Atribución-NoComercial-SinDerivadas
LÓGICA DIFUSA
In this paper three case studies are presented applying a Fuzzy-Evolutionary Multimodal approach to predict and optimize the prediction assembly time, this methodology can be a good complement of the design for assembly methodology of Boothroy-Dewhurst. This hybrid method analyzes different situations and conditions, identifies sources of variability that should be avoided during the process design because it increases the assembly time. The evolutionary algorithm searches the set of inputs or conditions in the fuzzy model and uses the predicted time to evaluate every set of inputs generated, the best tree conditions with and without constrains design are found by this approach. The research show the advantages of use a Fuzzy-Evolutionary Multimodal approach in order to analyze the variables behavior to predict, control and optimize the assembly time in the new product design.
2006
Artículo
Español
Empresas
Investigadores
Decision Support Systems Intelligent to Predict and Optimize the Assembly Time for New Product Design Using a Fuzzy-Evolutionary Multimodal Approach Pérez V. Pedro, Torres-Trevino Luis, Carrum S. Elias and Ramirez C. Sergio. Special Issue: Advances in Computer Science and Engineering. 2006. MÉXICO
INGENIERÍA Y TECNOLOGÍA
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publishedVersion - Versión publicada
Aparece en las colecciones: ARTÍCULOS/ CAPÍTULOS DE LIBRO / MEMORIAS DE CONGRESO

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