Developing a High-Precision Surface Roughness Model For X12m Steel Turning

Surface roughness is a critical parameter in evaluating the quality of machining processes in manufacturing. Constructing a surface roughness model during machining provides a basis for predicting surface roughness in specific scenarios. This study focused on developing a surface roughness model for hard turning of X12M steel. An experimental process was conducted with a total of fifteen experiments. These fifteen experiments were designed according to a Box-Behnken matrix. In each experiment, the values of three parameters—cutting speed, feed rate, and depth of cut—were varied. Surface roughness values were measured in each experiment, and subsequently, a surface roughness model was constructed. This model expresses the mathematical relationship between surface roughness and the three cutting parameters. A second surface roughness model was 1 also established using the Box-Cox transformation. The accuracy of these two models was compared through five parameters: R-squared coefficient, predicted R-squared coefficient, adjusted R-squared coefficient, Percentage Absolute Error (PAE), and Percentage Square Error (PSE). The results showed that all five parameters of the second model (the model using the Box-Cox transformation) were superior to the first model. In other words, the accuracy of the surface roughness model was improved by using the Box-Cox transformation to convert the data.