Optimization methodology of the quality of products
DOI:
https://doi.org/10.15381/idata.v18i2.12105Keywords:
artificial neural networks, design of experiments, fuzzy logic, genetic algorithms, uality optimizationAbstract
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.Downloads
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Copyright (c) 2015 Juan Manuel Cevallos Ampuero, Luis Raez Guevara
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