Surface roughness evaluation in machining titanium alloys using non-textured and textured cutting inserts

Abstract

Ti-6Al-4V alloy is well known for its difficulty in machining due to its ultimate hardness. The temperature generated at the tool-chip interface is typically high which results in poor surface finish and rapid tool wear. The current focus of work was to analyze the influence of response parameters such as cutting speed, feed rate and depth of cut on the surface roughness on the non-textured and textured cutting inserts. Response Surface Methodology (RSM) was utilized to generate the analytical relation between the process parameters and their interaction with the responses namely surface roughness. Analysis of Variance (ANOVA) was implemented to correlate with the significant factors and the correctness of the model. The machining was done experimentally using the textured and non-textured tools and the surface roughness was measured to analyze the influence of process parameters. It was found that the surface roughness was immensely reduced while using microtextured cutting tools.

Influence of cutting parameters on surface topography in high-speed milling of slots in titanium alloy TC4

“…The analysis of literature shows, that most of the studies on high-speed machining of Ti6Al4V concerns turning processes. Similar investigation [6] of influence of turning parameters on surface quality of Ti6Al4V samples has shown, that feed rate has greatest influence on surface quality -an increase in feed rate and decrease in rotating speed led to significant deterioration of surface roughness. Authors of the study [7] on hole drilling in TC4 alloy investigated influence of process parameters on surface quality and dimensional accuracy.…”

Estudio de consumos energéticos en los centros de mecanizado CNC Haas UMC-750 y Leadwell V-40iT®.

“…Se propone, por lo tanto, que para realizar un análisis comparativo entre centros de mecanizado o entre rutas de mecanizado considerar solo la potencia relacionada a la etapa de corte. Las variables a considerar en dicha etapa son la velocidad de corte, avance y profundidad las cuales conducen a una buena precisión en los modelos de predicción (5,(16)(17)(18)(19)(20) ; pero es necesario aumentar la cantidad de datos experimentales (5,15) . Los estudios centrados solo en el corte son importantes porque este parámetro influye directamente en la calidad superficial de la pieza mecanizada.…”

“…También se han relacionado el esfuerzo cortante, la energía de fricción (14) y la rugosidad (15) ; con lo que se puede inferir que es muy elevada la cantidad de variables y parámetros del proceso de mecanizado que tienen una influencia directa en el consumo energético y una alta interdependencia entre ellos, lo que indica que predecir el consumo es cada vez más complejo y sugiere la necesidad de estudios sistemáticos que ayuden a identificar las variables de mayor impacto. Behrendt et al (6) , midieron la potencia para el tiempo de espera o stand by de ocho diferentes centros de mecanizado clasificados según su capacidad de procesamiento (Ver Figura 2).…”