Enhancing post machining surface finish of titanium alloy by cutting parameter optimization using ANOVA analysis

Abstract Titanium alloys are categorised under difficult to machine materials. The machinability of titanium alloy, Ti6Al4V using statistical methods such as Analysis of Variance (ANOVA) is investigated in this paper. Ti6Al4V is the most widely used titanium alloy in aerospace and biomedical application due to its advantageous material properties. However, despite its wide-ranging applications, there is a lack of clarity concerning its ideal machining parameters. This ambiguity primarily stems from Ti6Al4V's inherent properties, notably its low thermal conductivity and high chemical reactivity. Understanding and optimizing the machining parameters to get the right combination of speed, feed, depth of cut and coolant condition is vital. To gather comprehensive insights, a series of machining trials were conducted at various combinations of cutting parameters. The effects of varying the selected parameters on a crucial machining performance indicators-surface roughness was considered. Orthogonal arrays, known for their robustness in experiment design, were chosen to structure the machining trials. Furthermore, to decipher the collected data and interpret the results, ANOVA techniques were utilized with the help of R programming. The insights garnered can lead to more streamlined machining strategies, ensuring higher productivity and efficiency. By bridging the knowledge gap, this research seeks to make machining titanium alloys simpler, cost effective and more efficient for manufacturers.