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Evaluation of surface roughness of novel Al-based MMCs using Box-Cox transformation
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Evaluation of surface roughness of novel Al-based MMCs using Box-Cox transformation
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Journal Article
Evaluation of surface roughness of novel Al-based MMCs using Box-Cox transformation
2024
Overview
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 L
9
orthogonal array. The process’s output characteristic was measured in terms of surface roughness (R
a
) 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 R
a
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.
Publisher
Springer Paris,Springer Nature B.V
