A study on the effect of energy input on spatter particles creation during selective laser melting process AITranslate
Abstract AITranslate
Selective laser melting (SLM) is a promising manufacturing technique for the production of complex metallic components. One of the crucial factors influencing the mechanical properties of the final product is spatter particles formation during the process. In this study, high- speed photography is utilized to record the formation mechanisms and the dynamic behavior of spatter particles. An image processing analysis framework is utilized to assess the distribution of spatter particles under various energy inputs. It is found that changing the laser scan velocity has more influences on spatter formation in comparison with the energy input. The relationship between the numbers of created spatter particles, induced unmelted regions and density variability are interpreted and discussed based on other observations, such as microscopic examination and density analysis of SLM parts. The obtained results could be used to enhance the current manufacturing process parameters optimization methods in SLM process.
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DOI:https://doi.org/10.1016/j.addma.2017.12.009
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Selective laser melting (SLM) is a promising manufacturing technique for the production of complex metallic components. One of the crucial factors influencing the mechanical properties of the final product is spatter particles formation during the process. In this study, high- speed photography is utilized to record the formation mechanisms and the dynamic behavior of spatter particles. An image processing analysis framework is utilized to assess the distribution of spatter particles under various energy inputs. It is found that changing the laser scan velocity has more influences on spatter formation in comparison with the energy input. The relationship between the numbers of created spatter particles, induced unmelted regions and density variability are interpreted and discussed based on other observations, such as microscopic examination and density analysis of SLM parts. The obtained results could be used to enhance the current manufacturing process parameters optimization methods in SLM process.
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| GB/T 7714-2015 | [1] Mohsen Taheri Andani, Reza Dehghani, Mohammad Reza KaramoozRavari, et al. Additive Manufacturing, 2018(20). DOI:10.1016/j.addma.2017.12.009. |
| MLA | [1] Mohsen Taheri Andani, et al., Additive Manufacturing, no. 20, 2018, https://doi.org/10.1016/j.addma.2017.12.009. |
| APA | [1] Mohsen Taheri Andani, Reza Dehghani, Mohammad Reza KaramoozRavari, Reza Mirzaeifar, & Jun Ni. (2018). Additive Manufacturing(20). https://doi.org/10.1016/j.addma.2017.12.009 |
| IEEE | [1] Mohsen Taheri Andani, Reza Dehghani, Mohammad Reza KaramoozRavari, Reza Mirzaeifar, and Jun Ni, Additive Manufacturing, no. 20, 2018, doi: 10.1016/j.addma.2017.12.009. |
