3D printing technologies have made rapid prototyping of previously unachievable structures a possibility. There are several types of 3D printing methodologies that are compatible with a range of materials, including everything from soft polymers to metals and food.1
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One approach to 3D printing is laser powder bed fusion. Laser power bed fusion printing, like all 3D printing methods, involves first taking a CAD model and slicing it into thin layers. The size of these slices or layers dictates how much powder will be deposited during each stage of the additive manufacturing process. Thinner layers allow better resolution structures but take significantly more printing time.
Once the layers have been defined, each stage of the printing process involves depositing a layer of powder and then scanning the area with a powerful laser beam to cause the powder to melt together to form a continuous region of solid metal.
Laser powder bed fusion is one of the most common additive manufacturing methods for metals as a good degree of precision can be achieved and it is one of the most affordable printing methods.
However, while very good results can be achieved with laser powder bed fusion method and the technique is particularly well-suited to printing highly complex structures, the method can leave sub-surface cracks in the material.
One of the biggest barriers to the adoption of additive manufacturing methods in the industry is uncertainties in product control3 and one of the key challenges for metal powder bed fusion approaches, in particular, is a more rigorous understanding of the physics involved in the melt processes so more accurate computational models can be used for optimizing processing conditions.2
The formation of sub-surface cracks is problematic as they reduce the strength and stability of the structure. Such cracks are not always observable by visual inspection either so different types of imaging methods need to be used as part of the post-manufacturing quality control.
Methods such as X-ray tomography are commonly used to inspect the inner structures and voids of 3D printing objects.4 Most 3D prints make use of internal voids in the structure as a way of reducing the mass of the final object, saving material and decreasing print times. As high-energy X rays can have good penetration depths even for metals, they can pass through the object to render a full 3D image of the internal structure.
While X-ray tomography is an excellent high-resolution non-destructive method and can provide detailed structural information on any defects present, it is costly and means parts need to be small enough to fit into the scanner. The use of X-ray radiation also involves additional safety considerations and makes it difficult to make the technique more portable for in situ measurements.
Recent work from the Lawrence Berkeley National laboratories has been exploring how the use of surface acoustic waves generated during ultrasound measurements could be used for non-destructive defect analysis.5 The team was able to demonstrate that surface acoustic waves could successfully detect both surface and internal defects that could also be detected by optical microscopy and X-ray computed tomography respectively.
Images are created from ultrasound measurements by reconstruction of the intensity of the reflected versus the incident ultrasonic waves. Depending on the density of the material, different amounts of absorption will occur, creating regions of contrast in the image.
Some of the advantages of ultrasound imaging methods include their robustness, affordability and capacity to provide 3D datasets at much quicker rates than X-ray tomographic methods.
Ultrasound machinery is also more portable and easily scaled to handle larger sample sizes. The improved data acquisition rate is important for use in additive manufacturing processes as this would potentially mean the defect analysis could be integrated into the manufacturing process itself.
The team generated their surface acoustic waves for performing the ultrasound measurements using a high-power Nd:YAG laser that acts as a thermoelastic source. Laser sources for ultrasound are ideal as the source characteristics tend to be highly controllable, and by using different optical setups, the team could control the shape of the output light for imaging.
With these new surface acoustic wave measurements, the team was able to detect different types of defects such as spatter and breaks between lines – common surface defects – as well as substructure voids where the material had not been successfully deposited.
Realizing the full potential of additive manufacturing as a fully automated process does rely on having diagnostic methods that are sufficiently rapid and easy to analyze. They can work ‘on the fly’ with limited to no human guidance.
One of the limitations of surface acoustic wave methods is the penetration depth of the wave is much less than that of X-ray radiation and so only voids 200 μm below the surface could be detected.
However, the ability to detect issues around melt lines – the region where each layer is deposited during the additive manufacturing process - and the enhanced measurement speed makes ultrasound an attractive prospect for future developments for online process inspection.
References and Further Reading
Nachal, N., Moses, J. A., Karthik, P., & Anandharamakrishnan, C. (2019). Applications of 3D Printing in Food Processing. Food Engineering Reviews, 11(3), 123–141. https://doi.org/10.1007/s12393-019-09199-8
King, W. E., Anderson, A. T., Ferencz, R. M., Hodge, N. E., Kamath, C., Khairallah, S. A., & Rubenchik, A. M. (2015). Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges. Applied Physics Reviews, 2(4), 041304. https://doi.org/10.1063/1.4937809
PWC, 3D Printing and the New Shape of Industrial Manufacturing (PricewaterhouseCoopers LLP, Delaware, 2014) https://www.pwc.se/en.html
Khosravani, M. R., & Reinicke, T. (2020). On the Use of X-ray Computed Tomography in Assessment of 3D-Printed Components. Journal of Nondestructive Evaluation, 39(4). https://doi.org/10.1007/s10921-020-00721-1
- Harke, K. J., Calta, N., Tringe, J., & Stobbe, D. (2022). Laser-based ultrasound interrogation of surface and sub-surface features in advanced manufacturing materials. Scientific Reports, 12(1), 1–11. https://doi.org/10.1038/s41598-022-07261-w
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