Being able to predict cutting forces, torque and power in machining applications allows to check their influence on the quality of the product, to assess the feasibility of the process and to compare different operations for sustainability purposes. In this paper, the analytical development of a mechanistic model for cutting forces prediction for high-feed mills is carried out. High-feed cutters are featured by extremely low lead angles, leading to a gradual engagement of the cutter inside the workpiece. This fact prevents the mechanistic literature formulation to accurately compute the undeformed instantaneous chip section of each cutter, and thus to correctly predict the spindle torque and power. A closed analytical formulation for the mechanistic cutting force model, including an improved chip thickness formulation with variable entry and exit angles and double-phased cutter geometry, is presented. Experimental cutting tests using double-phased high-feed mills were carried out on with variable feed rate per tooth, cutting speed and axial depth of cut. The model was assessed by comparing the performances of the literature model and the developed high-feed one in the identification of specific force coefficients — SFC. The identified SFC resulted to belong to two statistically different populations. SFC 95% confidence intervals were found to be significantly narrower with respect to the literature ones. 95% confidence intervals were equal to (1085; 1426) MPa and (970; 2423) MPa for the proposed and literature model, respectively. The validity of the proposed model was assessed in terms of mean forces, mean spindle torque and mean spindle power prediction capabilities. The Root Mean Squared Prediction Error for the proposed model resulted to be remarkably lower (15 N, 0.33 Nm, 29 W) with respect to literature model (41 N, 1.25 Nm, 120 W).

Mechanistic force model for double-phased high-feed mills

Bernini L.;Albertelli P.;Monno M.
2023-01-01

Abstract

Being able to predict cutting forces, torque and power in machining applications allows to check their influence on the quality of the product, to assess the feasibility of the process and to compare different operations for sustainability purposes. In this paper, the analytical development of a mechanistic model for cutting forces prediction for high-feed mills is carried out. High-feed cutters are featured by extremely low lead angles, leading to a gradual engagement of the cutter inside the workpiece. This fact prevents the mechanistic literature formulation to accurately compute the undeformed instantaneous chip section of each cutter, and thus to correctly predict the spindle torque and power. A closed analytical formulation for the mechanistic cutting force model, including an improved chip thickness formulation with variable entry and exit angles and double-phased cutter geometry, is presented. Experimental cutting tests using double-phased high-feed mills were carried out on with variable feed rate per tooth, cutting speed and axial depth of cut. The model was assessed by comparing the performances of the literature model and the developed high-feed one in the identification of specific force coefficients — SFC. The identified SFC resulted to belong to two statistically different populations. SFC 95% confidence intervals were found to be significantly narrower with respect to the literature ones. 95% confidence intervals were equal to (1085; 1426) MPa and (970; 2423) MPa for the proposed and literature model, respectively. The validity of the proposed model was assessed in terms of mean forces, mean spindle torque and mean spindle power prediction capabilities. The Root Mean Squared Prediction Error for the proposed model resulted to be remarkably lower (15 N, 0.33 Nm, 29 W) with respect to literature model (41 N, 1.25 Nm, 120 W).
2023
High-feed milling, Double-phased cutters, Specific force coefficients, Analytical mechanistic model, Mean cutting forces, Mean cutting torque and power
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1225933
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