Selective Laser Melting is one of the most widely used Additive manufacturing technologies for producing metal parts. Among the many advantages of SLM, the low build rate is still one of the most difficult challenges to address. The Build Rate (BR) of SLM depends on many factors, one of them is the scanning time which is directly related to Fluence. In this work, a procedure to select a process parameter combination with an increased BR is presented and validated experimentally. A357 alloy was selected to print tensile specimens using different combinations of process parameters resulting in the same value of Fluence, and four levels of Fluence are selected for the analysis. Despite the wide range of Fluence considered, 85–140 J/mm3, the mechanical properties did not change. The combination of parameters ensuring the highest productivity was selected for the validation run. Experimental data were used to estimate regression equations able to predict the mechanical properties of the high-productivity condition. Density and UTS of the validation samples were accurately predicted by the regression equations, and they were consistent with the base material properties. The procedure allowed us to identify a combination of parameters ensuring an increase in productivity of 26 % compared to the standard condition.
Improvement of SLM Build Rate of A357 alloy by optimizing Fluence
Cacace, S.;Semeraro, Q.
2021-01-01
Abstract
Selective Laser Melting is one of the most widely used Additive manufacturing technologies for producing metal parts. Among the many advantages of SLM, the low build rate is still one of the most difficult challenges to address. The Build Rate (BR) of SLM depends on many factors, one of them is the scanning time which is directly related to Fluence. In this work, a procedure to select a process parameter combination with an increased BR is presented and validated experimentally. A357 alloy was selected to print tensile specimens using different combinations of process parameters resulting in the same value of Fluence, and four levels of Fluence are selected for the analysis. Despite the wide range of Fluence considered, 85–140 J/mm3, the mechanical properties did not change. The combination of parameters ensuring the highest productivity was selected for the validation run. Experimental data were used to estimate regression equations able to predict the mechanical properties of the high-productivity condition. Density and UTS of the validation samples were accurately predicted by the regression equations, and they were consistent with the base material properties. The procedure allowed us to identify a combination of parameters ensuring an increase in productivity of 26 % compared to the standard condition.File | Dimensione | Formato | |
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