A Finite Element Model for Temperature Prediction in Laser-Assisted Milling of AerMet100 Steel

Abstract

Laser-assisted milling (LAM) represents an innovative process to enhance productivity in comparison with conventional milling. The workpiece temperature in LAM not only affects the cutting performance of materials, but also the machined surface quality of the part. This paper presents a 3D transient finite element (FE) model for workpiece temperature prediction in LAM. A moving Gaussian laser heat source model is implemented as a user-defined subroutine and linked to ABAQUS. The thermal model is validated by machining AerMet100 steel under different process parameters (laser power, spindle speed and feed per tooth). Good agreement between predicted and measured workpiece temperatures indicates that the FE model is feasible. In addition, the effects of laser spot size and incident angle on workpiece temperature are analyzed based on the proposed model. This work can be further applied to optimize process parameters for controlling the machined surface quality in LAM.