Metodología de optimización de la calidad de productos

In this study we have developed a method for optimizing the parameters of quality of products that consists of five steps: 1) Determine the characteristics of product quality and process variables 2) Develop an experimental design with Taguchi Methods 3) Develop experiments with Response Surface Met...

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Detalles Bibliográficos
Autores: Cevallos Ampuero, Juan Manuel, Raez Guevara, Luis
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:Perú
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Idioma:español
OAI Identifier:oai:revistasinvestigacion.unmsm.edu.pe:article/12105
Acceso en línea:https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/12105
Access Level:acceso abierto
Palabra clave:artificial neural networks
design of experiments
fuzzy logic
genetic algorithms
uality optimization
algoritmos genéticos
diseño de experimentos
lógica difusa
optimización de la calidad
redes neuronales artificiales
Descripción
Sumario:In this study we have developed a method for optimizing the parameters of quality of products that consists of five steps: 1) Determine the characteristics of product quality and process variables 2) Develop an experimental design with Taguchi Methods 3) Develop experiments with Response Surface Methodology. 4) Determine a neural network that represents the relationships between variables and quality characteristics. Using fuzzy variables if there is information not deterministic. 5) Optimize with the use of genetic algorithms. In this proposal, artificial neural networks ANN allow to estimate response functions; in the case of having the qualitative variables these are processed with fuzzy logic LD and in the optimization step genetic algorithms GA are used. An example of optimization with multiple responses is presented to verify the method.