X-ray CT analysis of the influence of process on defect in Ti-6Al-4V parts produced with Selective Laser Melting technology
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Selective Laser Melting (SLM) technology is a potential Additive Manufacturing (AM) process. It has the ability to manufacture metal parts with complex construction. However, there are always defects in SLM products due to the raw materials, manufacturing parameters, and post-treatment. To investigate the relationship between manufacturing process parameters and defects in SLM products, laser power and scan speed are selected as variable parameters to fabricate cube samples. The 3D information of each specimen are collected by X-ray computed tomography, including the size, morphology, and spatial distribution of defects. The mathematical model of laser power and scanning speed with defect volume fraction was established. The result shows that when the scanning speed is less than 1200 mm/s, the defect volume rate increases slowly, but when the scanning speed is faster than 1200 mm/s, the volume rate of defects increases rapidly. As the laser power increases, the volume rate of defect decreased initially and then followed by an increase. It can be concluded that there are many defects in the part manufactured by low laser power and high scanning speed parameter, and the same result by high laser power and high scanning speed parameter. Additionally, the defects are larger and some of them distribute along the scanning path in the latter. Besides, the process window for SLM Ti-6Al-4V is created for exposing the relationship between process parameters and defects, and volume-spherical scatters are used to characterize different process zones.
KeywordsSelective Laser Melting X-ray computed tomography Defect Process parameter
We would like to thank the anonymous reviewers for their constructive comments.
This work was financially supported by National Natural Science Foundation of China (51775273); National Commercial Aircraft Manufacturing Engineering Technology Research Center Innovation Fund Project (COMAC-SFGS-2018-37); Equipment Pre-research Fund (6141B07090119, 61409230305); National Defense Basic Research (JCKY2018605C010); and Jiangsu Province Science and Technology Support Plan Project, China (BE2018010-2);Guangdong Introducing Innovative and Enterpreneurial Teams (NO:2016ZT06G025); Guangdong Natural Science Foundation NO:2017B030306014.
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