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Abstract(s)
Na indĂșstria, um dos principais objetivos Ă© conseguir uma produção a baixo custo, com um tempo de fabrico o mais curto possĂvel e uma Ăłtima qualidade de produto. Para isso, a indĂșstria recorre Ă s mĂĄquinas de comando numĂ©rico (CNC), conseguindo assim minimizar o tempo de maquinagem e obter uma elevada precisĂŁo.
Estas måquinas, CNC, podem ser aplicadas a diferentes processos de maquinagem, nomeadamente, torneamento, fresagem, furação, entre outros. Sendo o mais utilizado a fresagem, devido à sua versatilidade. Por norma, este processo é utilizado para maquinar materiais metålicos, como é o caso do aço e dos ferros fundidos.
Para melhorar estes tipos de processos de maquinagem, Ă© necessĂĄrio realizar estudos que mostrem qual a influĂȘncia dos diferentes parĂąmetros no processo e que, concomitantemente, permitam escolher corretamente as ferramentas de corte mais adequadas para as operaçÔes de maquinagem. Neste trabalho estudou-se o efeito de quatro parĂąmetros do processo de fresagem (o tipo de pastilha, a velocidade de corte, o avanço e a penetração axial) na rugosidade superficial, no desgaste das pastilhas e na taxa de produção durante a maquinagem de um ferro fundido branco (de dureza 370 HB).
Para esta anĂĄlise foram usados dois mĂ©todos de otimização: o mĂ©todo de Taguchi e a anĂĄlise relacional de Grey. Com o mĂ©todo de Taguchi foi possĂvel determinar a matriz dos ensaios experimentais efetuados neste trabalho (L18) e, posteriormente, determinar a combinação Ăłtima de parĂąmetros para cada um dos elementos de controlo (rugosidade, desgaste das ferramentas e taxa de produção) individualmente, bem como, a influĂȘncia dos parĂąmetros nesses elementos de controlo. A anĂĄlise relacional de Grey foi utilizada para determinar a combinação Ăłtima de parĂąmetros para o conjunto dos elementos de controlo.
O critĂ©rio de paragem de paragem dos ensaios experimentais foi efetuado de acordo com a norma ISO 8688-1, e ocorreu quando as pastilhas atingissem um desgaste igual ou superior a 0.2 [mm]. Para cada paragem do ensaio foi medido o desgaste das pastilhas e a rugosidade superficial da peça. No final dos 18 ensaios experimentais, foi realizado um tratamento estatĂstico dos dados atravĂ©s da anĂĄlise de variĂąncia (ANOVA), com o intuito de determinar a influĂȘncia dos parĂąmetros na vida Ăștil das ferramentas de corte, na rugosidade superficial da peça e na taxa de produção. O valor mĂĄximo de vida Ăștil foi 222 [min], o valor mĂnimo da mĂ©dia da rugosidade foi 0,31 [ÎŒm] e o valor mĂĄximo da taxa de produção foi de 4,584 [cm3/min].
Recorrendo Ă anĂĄlise de variĂąncia foi possĂvel verificar que os parĂąmetros que mais influenciaram para a vida Ăștil, rugosidade e taxa de produção. Para o primeiro caso, para a vida Ăștil, o parĂąmetro que mais influenciou foi o avanço, com 41,32 %, enquanto para a rugosidade o que mais influenciou foi o tipo de pastilhas, com o valor de 90,85 %. No Ășltimo caso, na taxa de produção, existem trĂȘs parĂąmetros que influenciam da mesma forma, a velocidade de corte, o avanço e a penetração axial com 33,33 %.
O segundo mĂ©todo usado foi a anĂĄlise relacional de Grey que permitiu determinar a melhor combinação de parĂąmetros. Para realizar esta escolha foi necessĂĄrio decidir, numa gama de 0 a 1, a importĂąncia que Ă© dada Ă vida Ăștil, Ă rugosidade superficial e Ă taxa de produção, sendo que para este estudo os trĂȘs casos foram-lhes atribuĂdos 0,5. A melhor combinação obtida com este mĂ©todo foi: Pastilha 2, velocidade de corte igual a 150 [m/min], avanço igual a 0,1 [mm/dente] e a penetração axial de 0,3 [mm].
In industry, one of the main objectives is to achieve low cost production with the shortest possible manufacturing time and excellent product quality. For this, the industry uses the numerical control (CNC) machines, thus managing to minimize the machining time and obtain a high precision. These machines, CNC, can be applied to different machining processes, namely, turning, milling, drilling, among others. Being the most used milling, due to its versatility. As a rule, this process is used to machine metal materials, such as steel and cast irons. In order to improve these types of machining processes, it is necessary to carry out studies that show the influence of the different parameters in the process and, at the same time, allow to choose the cutting tools most suitable for the machining operations. In this work the effect of four parameters of the milling process (type of insert, cutting speed, feed rate and axial depth) on the surface roughness, the wear of the tools and the production rate during the machining of a cast white iron (hardness 370 HB). Two optimization methods were used for this analysis: the Taguchi method and the Gray relational analysis. With the Taguchi method, it was possible to determine the matrix of the experimental tests carried out in this work (L18) and later to determine the optimal combination of parameters for each of the control elements (roughness, tool wear and production rate) individually as well such as the influence of the parameters on these control elements. Gray relational analysis was used to determine the optimal combination of parameters for the control elements as a whole. The stop criterion of the experimental tests was carried out in accordance with ISO 8688-1 and occurred when the inserts reached a wear and tear equal to or greater than 0.2 [mm]. For each stop of the test the wear of the pellets and the surface roughness of the part were measured. At the end of the 18 experimental tests, a statistical treatment of the data was performed through analysis of variance (ANOVA), in order to determine the influence of the parameters on the useful life of the cutting tools, the surface roughness of the piece and the production rate. The maximum lifetime value was 222 [min], the minimum value of the the arithmetic average was 0.31 [ÎŒm] and the maximum value of the production rate was 4.584 [cm3/ min]. With the use of the analysis of variance it was possible to verify that the parameters that most influenced the useful life, roughness and production rate. For the first case, for the useful life, the parameter that most influenced was the advance, with 41.32%, while for the roughness the most influenced was the type of inserts, with the value of 90.85%. In the last case, the production rate, there are three parameters that influence in the same way, the cutting speed, the advance and the axial penetration with 33.33%. The second method used was Gray relational analysis that allowed to determine the best combination of parameters. In order to make this choice, it was necessary to decide, in a range of 0 to 1, the importance given to the useful life, the surface roughness and the production rate, and for this study the three cases were attributed 0.5. The best combination obtained with this method was: Table 2, shear rate equal to 150 [m / min], feed rate equal to 0.1 [mm / tooth] and axial depth of 0.3 [mm].
In industry, one of the main objectives is to achieve low cost production with the shortest possible manufacturing time and excellent product quality. For this, the industry uses the numerical control (CNC) machines, thus managing to minimize the machining time and obtain a high precision. These machines, CNC, can be applied to different machining processes, namely, turning, milling, drilling, among others. Being the most used milling, due to its versatility. As a rule, this process is used to machine metal materials, such as steel and cast irons. In order to improve these types of machining processes, it is necessary to carry out studies that show the influence of the different parameters in the process and, at the same time, allow to choose the cutting tools most suitable for the machining operations. In this work the effect of four parameters of the milling process (type of insert, cutting speed, feed rate and axial depth) on the surface roughness, the wear of the tools and the production rate during the machining of a cast white iron (hardness 370 HB). Two optimization methods were used for this analysis: the Taguchi method and the Gray relational analysis. With the Taguchi method, it was possible to determine the matrix of the experimental tests carried out in this work (L18) and later to determine the optimal combination of parameters for each of the control elements (roughness, tool wear and production rate) individually as well such as the influence of the parameters on these control elements. Gray relational analysis was used to determine the optimal combination of parameters for the control elements as a whole. The stop criterion of the experimental tests was carried out in accordance with ISO 8688-1 and occurred when the inserts reached a wear and tear equal to or greater than 0.2 [mm]. For each stop of the test the wear of the pellets and the surface roughness of the part were measured. At the end of the 18 experimental tests, a statistical treatment of the data was performed through analysis of variance (ANOVA), in order to determine the influence of the parameters on the useful life of the cutting tools, the surface roughness of the piece and the production rate. The maximum lifetime value was 222 [min], the minimum value of the the arithmetic average was 0.31 [ÎŒm] and the maximum value of the production rate was 4.584 [cm3/ min]. With the use of the analysis of variance it was possible to verify that the parameters that most influenced the useful life, roughness and production rate. For the first case, for the useful life, the parameter that most influenced was the advance, with 41.32%, while for the roughness the most influenced was the type of inserts, with the value of 90.85%. In the last case, the production rate, there are three parameters that influence in the same way, the cutting speed, the advance and the axial penetration with 33.33%. The second method used was Gray relational analysis that allowed to determine the best combination of parameters. In order to make this choice, it was necessary to decide, in a range of 0 to 1, the importance given to the useful life, the surface roughness and the production rate, and for this study the three cases were attributed 0.5. The best combination obtained with this method was: Table 2, shear rate equal to 150 [m / min], feed rate equal to 0.1 [mm / tooth] and axial depth of 0.3 [mm].
Description
Keywords
Vida Ăștil das ferramentas Ferramentas de fresagem