engleski

Predictive models for surface roughness of face milled S235JRG2 structural steel

In addition to the depth of cut, spindle speed and feed rate, the paper investigates the influence of the fourth input variable – way of cooling/lubricating (dry cutting conditions, cooling/lubricating through the tool and flood cooling/lubricating) on the surface roughness of face milled S235JRG2 structural steel. The results of the performed face-centered central composite design are shown in the form of regression models obtained from experimental data, the main aim being to represent the relationship between the roughness and input variables. In the obtained quadratic regression model, significant factors are the spindle speed, feed rate and cooling/lubricating, the interaction of linear spindle speed with cooling/lubricating and the quadratic terms of depth of cut and feed rate. Likewise, at each level of the cooling/lubricating factor, a quadratic model in the three factors is fitted.

Central composite design; Regression model; Surface roughness; S235JRG2 steel

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