부산대학교 도서관

Composites play a significant role in societal development. Therefore, the machining of composites is a significant topic of interest among the research community. In this context, this work uses stir-casted composite (Al-6061 alloy with graphene powder (5%), and nano-TiO2 (10%)) as a workpiece. Depth of cut, cutting speed, and feed rate were considered significant factors at three levels. The experimental design was formulated based on Taguchi's design of experiment (DOE) and used an L9 orthogonal array. The process’s output characteristic was measured in terms of surface roughness (Ra) using a Surface Roughness Tester. The regression analysis has been applied to determine the best process parameters with little trial and error. The likelihood estimator (lambda) was calculated using the Box-Cox transformation, yielding a powerful regression equation. The estimated values from the regression equation and the observed values were quite close to one another. A 0.687 Ra value was achieved with a 1 mm depth of cut, 1000 rpm spindle speed, and a 50 mm/min feed rate. To produce the smallest possible discrepancy between observed and anticipated values, the 'hyperparameter' of the regression equation was fine-tuned. The maximum likelihood estimator value of lambda was found to be 2, with a mean error of 0.03%. The variance inflation factor was also found to be 1.00, which justifies the correctness of the equation.