experimental and statistical investigations of surface roughness, vibration, and energy consumption values of titanium alloy during machining using response surface method and grey relational analysis

This study aims to explain the interaction between the results measured in the turning operation. for this purpose, ti 6al-4v alloy workpiece was machined on cnc lathe. surface roughness (ra), vibration and energy consumption values were determined by turning. experimental results were analyzed statistically. response surface method (rsm) and grey relational analysis were used statistical analysis. in rsm analysis, regression equations, anova, contour graphs, pertubation graphs, real and prediction graphs, % contribution graphs, most significant factor, optimum parameters, it is determined that the effective parameter in surface roughness, vibration and energy consumption is feed rate. grey relational analysis steps and results are examined.