Abstract
A low-cost parametric finite element thermal model is proposed to study the impact of the initial powder condition, such as diameter and packing density, on effective thermal conductivity as well as the impact of the laser power input on the final temperature distributions during selective laser melting (SLM). Stainless steel 304L is the material used, since it is not yet commercially available in SLM equipment and our main goal was to show the capabilities of the finite element method in the evaluation of power input in the process. The results from our sensitivity analysis showed that packing density has a greater impact on the final temperature distributions compared with powder diameter variance. However, overall the thermal conductivity of the powder only showed significant effects below the melting point, otherwise the thermal conductivity no longer affected the temperature distributions. Among the three different power inputs analyzed, the temperature profile demonstrated that power inputs of 100 and 200 W are recommended when printing SS-304L rather than 400 W, which generates too high temperature in the powder bed, a non-favorable behavior that can induce high residual stresses and material evaporation.
Highlights
Selective laser melting (SLM) is an additive manufacturing process that uses metal powder to build full-density parts in a layer-by-layer fashion
Since SLM uses a bed filled with a fine metal powder layered over a substrate, this process has become associated with the powder bed fusion (PBF) process
Results obtained in this study have shown that the energy absorption for all cases is directly attributed to the difference between stress distributions and the local stress concentrations [18]
Summary
Selective laser melting (SLM) is an additive manufacturing process that uses metal powder to build full-density parts in a layer-by-layer fashion. Shaw and Dai [15] developed coupled thermo-mechanical models for multi-material behavior and analyzed residual stresses; Cheng et al [16] investigated residual stresses and the deformation of a multi-layer model using different scanning strategies; and Vastola et al [17] conducted a parameter analysis on the final residual stresses state when performing a single track using TiAl6V4. Based on a comprehensive literature study, the proposed model’s main objective is to demonstrate the high capability of FEM, utilizing for that a low computational cost parametric thermal model able to predict temperature distributions when scanning a single layer and track of the powder bed. The powder diameter and the packing density are the focuses here, in order to determine the impact on the temperature profile during three sets of power input sources
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