Abstract

Hybrid machining processes using additional energy sources such as laser assisted machining (LAM) have increased considerably during the last years. The benefits of LAM for reducing tool wear and cutting forces are well known, especially for superalloys. However, optimal machining results depend on both the laser parameters and the cutting process parameters. It is difficult to find optimal LAM settings due to the complexity of the influencing parameters and their mutual interactions. The aim of the paper is to characterize the laser heating process by detecting how the individual LAM parameters influence working temperature, heat affected zone (HAZ) extension and laser track width. A reliable application requires a localized and controlled continuous heating of the material within the machining zone directly in front of the tool contact area. In this research statistical and technological knowledge is fully involved in the experimental activities. Therefore, a statistical study based on design of experiment (DoE) was carried out in order to investigate the effects of laser process parameters and their interactions. In practice, two-level fractional factorial design and analysis of variance (ANOVA) were applied. The following process parameters were examined: laser power, scanning speed, defocus (the distance between focal point and workpiece surface), temperature controlled by pyrometer, and surface roughness. Furthermore, a Finite Element (FE) model was developed based on experimental results in order to find out the optimal parameters for modeling the laser heating process. Future FE simulations of the laser assisted cutting processes will be carried out using this model of the moving laser source.

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