Abstract
The parameter sets used during the selective laser melting (SLM) process directly affect the final product through the resulting melt-pool temperature. Achieving the optimum set of parameters is usually done experimentally, which is a costly and time-consuming process. Additionally, controlling the deviation of the melt-pool temperature from the specified value during the process ensures that the final product has a homogeneous microstructure. This study proposes a multiphysics numerical model that explores the factors affecting the production of parts in the SLM process and the mathematical relationships between them, using stainless steel 316L powder. The effect of laser power and laser spot diameter on the temperature of the melt-pool at different scanning velocities were studied. Thus, mathematical expressions were obtained to relate process parameters to melt-pool temperature. The resulting mathematical relationships are the basic elements to design a controller to instantly control the melt-pool temperature during the process. In the study, test samples were produced using simulated parameters to validate the simulation approach. Samples produced using simulated parameter sets resulting in temperatures of 2000 K and above had acceptable microstructures. Evaporation defects caused by extreme temperatures, unmelted powder defects due to insufficient temperature, and homogenous microstructures for suitable parameter sets predicted by the simulations were obtained in the experimental results, and the model was validated.
Highlights
Additive manufacturing (AM) technology builds parts layer by layer using powders as a medium in 3D printers
The mathematical relationships between parameters are used to give an overview of the laser-powder interaction, which reduces the need to simulate for each set of parameters
These equations could be potentially used to overcome the challenge of experimental testing for each set of parameters to obtain the appropriate sets of parameters for production
Summary
Additive manufacturing (AM) technology builds parts layer by layer using powders as a medium in 3D printers. What are still missing, are the various process parameter sets and the mutual relationships between them These have been obtained via a reliable model that presents us the temperature values considering the melt process’s effective aspects. Metals 2021, 11, 1076 ness allocate a special space for them in additive manufacturing, and 316L stainless steel, as austenitic steel, stands out with its perfect resistance to oxidation at high temperatures while maintaining a low coefficient of thermal expansion, creep resistance, resistance to fatigue, and heat resistance [18,19,20,21] Based on these issues, the paper develops vast sets of the process parameters and the mathematical relationship between them for suitable and controllable fabrication using stainless steel 316L powder. These mathematical relationships could be used as the basic elements in the controller design of the 3D printer machine to control the melt-pool temperature during the process
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