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Selective laser melting (SLM) is an additive manufacturing technique designed to use a high power-density laser to melt and fuse metallic powder to fabricate complex parts with high accuracy. The accuracy and the functional properties of the fabricated part are greatly dependent on the process parameters. Thus, depending on the desired properties and the material, the parameters need to be optimized before fabrication. The processing parameters that control the SLM process comprise of the laser power, scan speed, hatch spacing, layer thickness and scan strategy. These process parameters are dependent on each other and therefore make the task of optimizing the process parameters an important one. This research is concerned with the optimization of several process parameters as well as the development of a model to predict the best properties for Inconel 718 superalloy. This study uses the Design of Experiment (DOE) system coupled with the full factorial Composite Central Design (CCD) of the Response Surface Methodology (RSM) to perform the regression analysis on laser power, scanning speed, and hatch spacing in order to predict the CAD model deviation, hardness values, and, variation in the phase composition using X-ray Diffraction (XRD). The simulated models obtained using the RSM technique were then analyzed. These results provided valuable information and helped us in controlling the functional properties of the fabricated part.
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