An integrated approach for additive manufacturing process planning: Selective Laser Melting

In many industrial applications, Laser Powder Bed Fusion Technology (LPBF) commercially well-known Selective laser melting (SLM) has been recognized for its flexibility in Net Shape Manufacturing. Where a feedstock is deposited and selectively fused with a thermal joining via laser power. In this work, an overview and integrated approach for the additive manufacturing process planning is presented. The unit process life cycle inventory (UPLCI) was used to discretize energy consumption and material losses for modeling the SLM process. A reusable perspective in terms of materials, parameters, and calculation tools to estimate the energy consumption and mass loss in practical evaluations of production lines is presented. Calculations of energy were obtained and classified as basic, idle, and active energy. Theoretical equations were also shown to relate the most important parameters of the process with its energy consumption. On the other hand, the optimization and characterization of parts for the processing parameters calibration in LPBF has been recently well studied in academia, but still under research in the industry, due to the early adoption of this technology in different companies and research centers. For this reason, a process planning workflow for the obtention of calibrated ranges of parameters for AISI 316L samples, and to understand the relationship between the improved parameters, the surface quality and part integrity with the microstructural characteristics. Two principal methods of characterization, (1) Nanoindentation and Electron backscatter diffraction (EBSD) and (2) non-contact profilometry by Focus Variation, were used to validate the influence of the overlap of the point distance (PD) and hatch distance (HD) in the fabrication process. In this study, hardness and the modulus of elasticity exhibited the highest values of 4.59 GPa and 229.7 GPa respectively in the parallel orientation to the build direction. The obtained hardness and modulus of elasticity were correlated with the different grain sizes and the resulting crystallographic orientation product of the thermal history of the process. Roughness (Ra) was improved with the selection of parameters and presented the lowest value of 5.433 μm. Finally, the microstructure was studied on the samples as the final assessment on the improved parameters where finer cellular/dendritic structures were found. At the end, a series of case studies were presented at the end to validate the use of these two-process planning methodology in the medical device applications.