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Resumo(s)
A crescente procura das indústrias por melhorias da eficiência produtiva tem se tornado,
cada vez mais, um incentivador ao aumento investigação com foco na otimização
de processos para o aumento da qualidade ao menor tempo e custo possível. Nesse cenário,
o setor industrial tem procurado sistemas inteligentes, capazes de auxiliar no suporte
à decisão, como parte de seus negócios e planos de crescimento. No presente trabalho,
desenvolveu-se um software baseado no método de otimização de superfícies de resposta
combinado com o algoritmo genético para apoiar a identificação de parâmetros ótimos
para a diminuição dos níveis vibratórios no processo de fresagem numa CNC. O software
prevê os parâmetros de fresagem - velocidade de corte, velocidade de avanço, penetração
axial e radial - que resultariam nos menores níveis de vibração e, consequentemente
resultando no aumento da qualidade superficial da peça produzida.
A fim de comprovar a fiabilidade do software de otimização, comparou-se os resultados
obtidos com os melhores resultados experimentais, obtidos anteriormente pelo método de
Taguchi. Da comparação verificou-se a fiabilidade da solução proposta.
The growing demand from industries for improvements in production efficiency has increasingly become an incentive to increase research focused on optimizing processes to increase quality in the shortest possible time and at the lowest possible cost. In this scenario, the industrial sector has been looking for intelligent systems capable of assisting in decision support as part of its business and growth plans. In the present work, software based on the method of optimization of response surfaces combined with a genetic algorithm has been developed to support the identification of optimal parameters for reducing vibration levels in the milling process in a CNC. The software predicts the milling parameters - cutting speed, feed speed, axial and radial penetration - which would result in the lowest vibration levels and consequently, increasing the surface quality of the produced part. In order to prove the reliability of the optimization software, the results obtained were compared with the best experimental results, previously obtained by the Taguchi method. From the comparison, the reliability of the proposed solution was verified.
The growing demand from industries for improvements in production efficiency has increasingly become an incentive to increase research focused on optimizing processes to increase quality in the shortest possible time and at the lowest possible cost. In this scenario, the industrial sector has been looking for intelligent systems capable of assisting in decision support as part of its business and growth plans. In the present work, software based on the method of optimization of response surfaces combined with a genetic algorithm has been developed to support the identification of optimal parameters for reducing vibration levels in the milling process in a CNC. The software predicts the milling parameters - cutting speed, feed speed, axial and radial penetration - which would result in the lowest vibration levels and consequently, increasing the surface quality of the produced part. In order to prove the reliability of the optimization software, the results obtained were compared with the best experimental results, previously obtained by the Taguchi method. From the comparison, the reliability of the proposed solution was verified.
Descrição
Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do Paraná
Palavras-chave
Otimização Algoritmo genético Software Fresagem