Computed tomography (CT) and additive manufacturing (AM) go hand-in-hand. As the technologies used in AM continue to evolve, CT plays a crucial role in accelerating process development by enabling 3D visualization of additively manufactured parts.
This article takes an in-depth look at some of the ways advanced CT is solving problems in additive manufacturing.
Additive manufacturing techniques offer unparalleled flexibility in manufacturing, enabling the fabrication of complex parts that would be prohibitively difficult or expensive to create via conventional machining methods. These include multi-material components and objects with complex internal features such as chambers and channels.1,2
CT enables detailed 3D imaging of additively manufactured parts – something that is not just useful, but necessary for the creation of certain complex parts via AM. CT is essential not only in quality control, where undesirable features such as pores or delamination may occur; but in the development of new AM parts and processes.3,4
Advancing CT for AM Applications
CT and AM continue to co-evolve, with next-generation AM applications providing a catalyst for the development of new CT technologies. North Star Imaging invests heavily in the research and development of CT processes to improve speed, precision, and versatility.
Increasing Throughput with Robotics
A need for increased throughput and automation in the industry has led to the incorporation of robotics into CT systems. Robots deployed inside the CT cabinet can pick up parts and automatically position them with respect to the X-ray tube, giving enhanced mobility and eliminating the need to open the cabinet door for manual manipulation.
Robots external to the cabinet can be used to load parts into the CT scanner, increasing throughput rate and paving the way toward fully automated in-line CT.
Imaging Large or Complex Objects with High-Energy CT
While medical X-ray tubes don’t exceed roughly 150 keV, industrial CT applications can call for energies into the MeV range. Even parts with relatively thin walls can have tangents or regions of high thickness which require increase X-ray penetration.
For example, a 10” diameter steel tube with a ¼” wall thickness actually requires X-ray penetration of several inches when imaging tangentially to the surface.
High energy CT enables increased material penetration for thicker materials and also for unusual geometries with variations in material thickness. This is particularly useful for AM applications, enabling 360º imaging of complex parts made from a variety of materials.
Taking multiple CT scans in rapid succession can enable the capture of dynamic volumetric information. This 4D CT essentially yields a video recording of an object's internal and external structures, enabling dynamic functionality to be studied in detail.
VorteX and Mosaic CT for Elongated and Large Parts
Elongated objects traditionally cannot fit into a single CT exposure. VorteX CT is a new development in industrial CT which uses spiral acquisition and reconstruction with a flat-panel detector to scan elongated parts in a single pass.
As well as significantly improving throughput, VorteX eliminates the cone angle artifacts caused by planar features in conventional non-spiral CT techniques. This makes it particularly useful for detecting delamination in AM tall parts, which are deposited in vertical layers.
MosaiX makes use of a manipulator and proprietary image-stitching algorithm to produce seamless images of large parts. MosaiX overcomes the limited field of view of the detector to produce CT scans as large as the cabinet can accommodate.
The Future of CT in Additive Manufacturing
As CT enables the development of new additive processes, AM demands more functionality and higher performance levels from CT. The benefits of CT for AM applications have been huge – and as we continue to overcome the challenges of imaging AM parts in greater detail, we expect these benefits to continue.
Ongoing challenges for CT include the development of algorithms to reduce scattering and other imaging artifacts. AI and machine learning may play an important role in the future, for example, training an AI to recognize and correct artifacts can improve CT image quality.5
North Star Imaging has been leading innovation in industrial CT for over 30 years. Our CT solutions and systems continue to provide unparalleled levels of insight for industrial applications, especially for additive manufacturing. To find out how your AM processes could benefit from CT, get in touch with us today.
- Dehue, R. The Possibilities of Weight Reduction With Additive Manufacturing. (2016).
- Joyce, J. Additive manufacturing paths to performance, innovation, and growth. (2012).
- Kruth, J. P. et al. Computed tomography for dimensional metrology. CIRP Annals 60, 821–842 (2011).
- Thompson, A., Maskery, I. & Leach, R. K. X-ray computed tomography for additive manufacturing: a review. Meas. Sci. Technol. 27, 072001 (2016).
- Park, H. S., Lee, S. M., Kim, H. P. & Seo, J. K. Machine-learning-based nonlinear decomposition of CT images for metal artifact reduction. arXiv:1708.00244 [physics] (2017).
This information has been sourced, reviewed and adapted from materials provided by North Star Imaging, Inc.
For more information on this source, please visit North Star Imaging, Inc.