Heat input modeling and calibration in dry NC-milling processes

Schweinoch, M.1, a; Joliet, R.1, b; Kersting, P.1, c; Zabel, A.1, d

Institut für Spanende Fertigung, Technische Universität Dortmund, Baroper Str. 303, 44227 Dortmund

a) schweinoch@isf.de; b) joliet@isf.de; c) petra.kersting@isf.de; d) zabel@isf.de


Due to friction and material deformation in the shear zone, workpieces in NC-milling processes are subjected to heat input and thermal loading. Ongoing geometric changes as well as time-varying contact and cutting conditions result in an inhomogeneous temperature field that is constantly in flux. Such thermally loaded workpieces often exhibit complex and transient thermomechanical deformations, which may result in erroneous material removal with respect to the desired shape. In order to meet critical manufacturing tolerances, it is therefore necessary to avoid and compensate these effects. Predicting the deformation exhibited by a thermally loaded workpiece is a problem of linear thermoelasticity, which can be solved by use of the finite element (FE) method. A prerequisite to this is the accurate calculation of the temperature field that results within the workpiece material during the course of the milling process. Although the FE method may be used for this as well, the practical application to realistic milling processes is limited due to the required computational resources. This paper presents a fast geometric process simulation for the prediction of cutting forces, heat input and thermal loading in dry NC milling. The temperature field of the workpiece is continuously updated, such that it is possible to determine the temperature of any material point at any point in time of the milling process. Individual models comprising the simulation system are described in detail, along with the experiments that are required to calibrate them. The accuracy of the geometric process simulation is validated by comparison with experimental data for a non-trivial milling process.


Geometric modeling, Temperature, Thermal error, Predictive model, Milling


Production Engineering. Research and Development, 9 (2015) 4, S. 495-504, ISSN 0944-6524 , doi: 10.1007/s11740-015-0621-z