| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.79 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
A indústria busca aumentar a produtividade com qualidade elevada em menor tempo, recorrendo frequentemente a máquinas de comando numérico (CNC) para alcançar esses objetivos.
Este estudo analisou a rugosidade superficial e a taxa de produção no fresamento do alumínio 5083 H111, variando o caminho de ferramenta e três parâmetros de usinagem: velocidade de corte, avanço por dente e profundidade de corte. Utilizou-se o método de Taguchi e a análise relacional de Grey para determinar a combinação ideal de parâmetros e avaliar a influência de cada um. Para o caminho de ferramenta ZigZag (Amostra Z) foi obtida a combinação A3B1C3, correspondente a uma velocidade de corte de 150 [m/min], avanço por dente de 0,035 [mm/rot] e profundidade de corte de 2,0 [mm]. Para o caminho de ferramenta Parallel Spiral (Amostra S) foi obtida a combinação A3B3C1, com uma velocidade de corte de 150 [m/min], avanço por dente de 0,025 [mm/rot] e profundidade de corte de 1,0 [mm]. Para o caminho de ferramenta
OneWay (Amostra O) foi obtida a combinação A1B3C3, ou seja, uma velocidade de corte de 50 [m/min], avanço por dente de 0,025 [mm/rot] e profundidade de corte de 2,0 [mm]. A ANOVA revelou que a velocidade de corte foi o parâmetro mais influente nos caminhos ZigZag e Parallel Spiral, enquanto o avanço por dente foi mais influente no caminho OneWay. O estudo demonstrou a eficácia dos métodos de otimização aplicados, permitindo identificar as melhores condições para maximizar a qualidade e a produtividade no fresamento do alumínio 5083 H111.
The industry seeks to increase productivity with high quality in less time, frequently resorting to numerical control machines (CNC) to achieve these goals. This study analyzed the surface roughness and production rate in milling aluminum 5083 H111, varying the tool path and three machining parameters: cutting speed, feed per tooth, and cutting depth. The Taguchi method and Grey relational analysis were used to determine the optimal combination of parameters and to assess the influence of each. For the ZigZag toolpath (Sample Z), the combination A3B1C3 was obtained, corresponding to a cutting speed of 150 [m/min], a feed per tooth of 0.035 [mm/rev], and a cutting depth of 2.0 [mm]. For the Parallel Spiral toolpath (Sample S), the combination A3B3C1 was obtained, with a cutting speed of 150 [m/min], a feed per tooth of 0.025 [mm/rev], and a cutting depth of 1.0 [mm]. For the OneWay toolpath (Sample O), the combination A1B3C3 was obtained, that is, a cutting speed of 50 [m/min], a feed per tooth of 0.025 [mm/rev], and a cutting depth of 2.0 [mm]. ANOVA revealed that cutting speed was the most influential parameter for the ZigZag and Parallel Spiral paths, while feed per tooth was more influential for the OneWay path. The study demonstrated the effectiveness of the applied optimization methods, allowing the identification of the best conditions to maximize quality and productivity in milling aluminum 5083 H111.
The industry seeks to increase productivity with high quality in less time, frequently resorting to numerical control machines (CNC) to achieve these goals. This study analyzed the surface roughness and production rate in milling aluminum 5083 H111, varying the tool path and three machining parameters: cutting speed, feed per tooth, and cutting depth. The Taguchi method and Grey relational analysis were used to determine the optimal combination of parameters and to assess the influence of each. For the ZigZag toolpath (Sample Z), the combination A3B1C3 was obtained, corresponding to a cutting speed of 150 [m/min], a feed per tooth of 0.035 [mm/rev], and a cutting depth of 2.0 [mm]. For the Parallel Spiral toolpath (Sample S), the combination A3B3C1 was obtained, with a cutting speed of 150 [m/min], a feed per tooth of 0.025 [mm/rev], and a cutting depth of 1.0 [mm]. For the OneWay toolpath (Sample O), the combination A1B3C3 was obtained, that is, a cutting speed of 50 [m/min], a feed per tooth of 0.025 [mm/rev], and a cutting depth of 2.0 [mm]. ANOVA revealed that cutting speed was the most influential parameter for the ZigZag and Parallel Spiral paths, while feed per tooth was more influential for the OneWay path. The study demonstrated the effectiveness of the applied optimization methods, allowing the identification of the best conditions to maximize quality and productivity in milling aluminum 5083 H111.
Descrição
Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do Paraná
Palavras-chave
CNC Rugosidade superficial Taxa de produção Fresamento Taguchi Análise relacional de grey ANOVA Otimização