IJAT Vol.14 No.3 pp. 439-446
doi: 10.20965/ijat.2020.p0439


Development of an Additive Manufactured Artifact to Characterize Unfused Powder Using Computed Tomography

Ahmed Tawfik, Paul Bills, Liam Blunt, and Radu Racasan

EPSRC Future Advanced Metrology Hub, University of Huddersfield
Queensgate, Huddersfield, West Yorkshire HD1 3DH, United Kingdom

Corresponding author

January 22, 2019
January 14, 2020
May 5, 2020
unfused powder, defects analysis, additive manufacturing, computed tomography

Additive manufacturing (AM) is recognized as a core technology for producing high-value components. The production of complex and individually modified components, as well as prototypes, gives additive manufacturing a substantial advantage over conventional subtractive machining. For most industries, some of the current barriers to implementing AM include the lack of build repeatability and a deficit of quality assurance standards. The mechanical properties of the components depend critically on the density achieved. Therefore, defect/porosity analysis must be carried out to verify the components’ integrity and viability. In parts produced using AM, the detection of unfused powder using computed tomography is challenging because the detection relies on differences in density. This study presents an optimized methodology for differentiating between unfused powder and voids in additive manufactured components, using computed tomography. Detecting the unfused powder requires detecting the cavities between particles. Previous studies have found that the detection of unfused powder requires a voxel size that is as small as 4 μm3. For most applications, scanning using a small voxel size is not reasonable because of the part size, long scan time, and data analysis. In this study, different voxel sizes are used to compare the time required for scanning, and the data analysis showing the impact of voxel size on the detection of micro defects. The powder used was Ti6Al4V, which has a grain size of 45–100 μm, and is typically employed by Arcam electron beam melting (EBM) machines. The artifact consisted of a 6 mm round bar with designed internal features ranging from 50 μm to 1400 μm and containing a mixture of voids and unfused powder. The diameter and depth of the defects were characterized using a focus variation microscope, after which they were scanned using a Nikon XTH225 industrial CT to measure the artifacts and characterize the internal features for defects/pores. To reduce the number of the process variables, the measurement parameters, such as filament current, acceleration voltage, and X-ray filtering material and thickness were kept constant. The VGStudio MAX 3.0 (Volume Graphics, Germany) software package was used for data processing, surface determination, and defects/porosity analysis. The main focus of this study is to explore the optimal methods for enhancing the detection of pores/defects while minimizing the time taken for scanning, data analysis, and determining the effects of noise on the analysis.

Cite this article as:
A. Tawfik, P. Bills, L. Blunt, and R. Racasan, “Development of an Additive Manufactured Artifact to Characterize Unfused Powder Using Computed Tomography,” Int. J. Automation Technol., Vol.14 No.3, pp. 439-446, 2020.
Data files:
  1. [1] T. Tateno, A. Kakuta, H. Ogo, and T. Kimoto, “Ultrasonic Vibration-Assisted Extrusion of Metal Powder Suspension for Additive Manufacturing,” Int. J. Automation Technol., Vol.12, No.5, pp. 775-783, 2018.
  2. [2] J. Lambert, A. Chambers, I. Sinclair, and S. Spearing, “3D damage characterisation and the role of voids in the fatigue of wind turbine blade materials,” Composites Science and Technology, Vol.72, No.2, pp. 337-343, 2012.
  3. [3] AP&C, “Powders designed for Additive Manufacturing.”  [Accessed December 13, 2017]
  4. [4] “Selective Laser Melting Machine SLM 500 – SLMSolutions.” [Accessed December 13, 2017]
  5. [5] P. Edwards and M. Ramulu, “Fatigue performance evaluation of selective laser melted Ti-6Al-4V,” Materials Science and Engineering: A, Vol.598, pp. 327-337, 2014.
  6. [6] N. Chawla, B. Jester, and D. T. Vonk, “Bauschinger effect in porous sintered steels,” Materials Science and Engineering: A, Vol.346, Issues 1-2, pp. 266-272, 2003.
  7. [7] S. J. Polasik, J. J. Williams, and N. Chawla, “Fatigue crack initiation and propagation of binder-treated powder metallurgy steels,” Metall. and Mat. Trans. A, Vol.33, pp. 73-81, 2002.
  8. [8] N. Chawla, X. Deng, M. Marrucci, and K. S. Narasimhan, “Effect of Porosity on the Microstructure and Mechanical Behavior of Powder Metallurgy Fe-Mo-Ni Steels,” Proc. of the 2003 Int. Conf. on Powder Metallurgy & Particulate Materials, pp. 7-257-7-269, 2003.
  9. [9] N. Chawla and X. Deng, “Microstructure and mechanical behavior of porous sintered steels,” Materials Science and Engineering: A, Vol.390, Issues 1-2, pp. 98-112, 2005.
  10. [10] D. Eylon and J. A. Hall, “Fatigue behavior of beta processed titanium alloy IMI 685,” Metallurgical Trans. A, Vol.8, No.6, pp. 981-990, 1977.
  11. [11] E. Brandl, U. Heckenberger, V. Holzinger, and D. Buchbinder, “Additive Manufactured AlSi10Mg Samples Using Selective Laser Melting (SLM): Microstructure, High Cycle Fatigue, and Fracture Behavior,” Materials and Design, Vol.34, pp. 159-169, 2012.
  12. [12] D. Eylon, “Fatigue crack initiation in hot isostatically pressed Ti-6Al-4V castings,” J. of Materials Science, Vol.14, No.8, pp. 1914-1922, 1979.
  13. [13] D. K. Xu, L. Liu, Y. B. Xu, and E. H. Han, “The crack initiation mechanism of the forged Mg-Zn-Y-Zr alloy in the super-long fatigue life regime,” Scripta Materialia, Vol.56, Issue 1, pp. 1-4, 2007.
  14. [14] H. Jiang, P. Bowen, and J. F. Knott, “Fatigue performance of a cast aluminium alloy Al-7Si-Mg with surface defects,” J. of Materials Science, Vol.34, No.4, pp. 719-725, 1999.
  15. [15] H. T. Pang and P. A. S. Reed, “Microstructure effects on high temperature fatigue crack initiation and short crack growth in turbine disc nickel-base superalloy Udimet 720Li,” Materials Science and Engineering: A, Vol.448, Issues 1-2, pp. 67-79, 2007.
  16. [16] M. J. Couper, A. E. Neeson, and R. J. Griffiths, “Casting Defects and the Fatigue Life of an Aluminum Casting Alloy,” Fatigue Fract. Engng. Mater. Struct., Vol.13, No.3, pp. 213-227, 1990.
  17. [17] C.-H. Ting, “A Model for the Long-Life Fatigue Behaviour of Small Notches,” Ph.D. thesis, University of Illinois at Urbana-Champaign, 1991.
  18. [18] J. F. Major, “Porosity control and fatigue behavior in A 356-T 61 aluminum alloy,” Trans.-American Foundrymens Society, pp. 901-906, 1998.
  19. [19] R. Hanke, T. Fuchs, and N. Uhlmann, “X-ray based methods for non-destructive testing and material characterization,” Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol.591, Issue 1, pp. 14-18, 2008.
  20. [20] H. Fujimoto, M. Abe, S. Osawa, O. Sato, and T. Takatsuji, “Development of Dimensional X-Ray Computed Tomography,” Int. J. Automation Technol., Vol.9, No.5, pp. 567-571, 2015.
  21. [21] A. Tawfik, S. Nicholson, R. Racasan, L. Blunt, and P. Bills, “Utilizing Detector Filters for Noise Reduction in X-Ray Computer Tomography Scanning for the Inspection of the Structural Integrity of Additive Manufactured Metal Parts,” Smart and Sustainable Manufacturing Systems, Vol.3, No.1, pp. 18-30, 2019.
  22. [22] W. C. Scarfe, A. G. Farman, and P. Sukovic, “Clinical applications of cone-beam computed tomography in dental practice,” J. Can. Dent. Assoc., Vol.72, No.1, pp.75-80, 2006.
  23. [23] J. Kastner, B. Harrer, G. Requena, and O. Brunke, “A comparative study of high resolution cone beam X-ray tomography and synchrotron tomography applied to Fe- and Al-alloys,” NDT and E Int., Vol.43, Issue 7, pp. 599-605, 2010.
  24. [24] O. Brunke, K. Brockdorf, S. Drews, B. Müller, T. Donath, J. Herzen, and F. Beckmann, “Comparison between X-ray tube based and synchrotron radiation based μCT,” Proc. of SPIE, Vol.7078, 70780U, 2008.
  25. [25] A. Tawfik, P. Bills, L. Blunt, and R. Racasan, “Characterisation of powder-filled defects in additive manufactured surfaces using X-ray CT,” Proc. of 8th Conf. on Industrial Computed Tomography (iCT2018), Wels, Austria, 2018, 119, 2018.
  26. [26] S. Vock et al., “Powders for powder bed fusion: a review,” Progress in Additive Manufacturing, Vol.4, No.4, pp. 383-397, 2019.
  27. [27] J. Yagüe-Fabra, S. Ontiveros, R. Jiménez, S. Chitchian, G. Tosello, and S. Carmignato, “A 3D edge detection technique for surface extraction in computed tomography for dimensional metrology applications,” CIRP Annals, Vol.62, Issue 1, pp. 531-534, 2013.
  28. [28] F. B. de Oliveira, A. Stolfi, M. Bartscher, L. De Chiffre, and U. Neuschaefer-Rube, “Experimental investigation of surface determination process on multi-material components for dimensional computed tomography,” Case Studies in Nondestructive Testing and Evaluation, Vol.6, Part B, pp. 93-103, 2016.
  29. [29] C. Song, P. Wang, and H. A. Makse, “A phase diagram for jammed matter,” Nature, Vol.453, No.7195, pp. 629-632, 2008.
  30. [30] Y. Stoyan and G. Yaskov, “Packing congruent hyperspheres into a hypersphere,” J. of Global Optimization, Vol.52, No.4, pp. 855-868, 2012.
  31. [31] J. H. Conway and J. J. A. Sloane, “Sphere Packings, Lattices, and Groups (2nd ed.),” Springer-Verlag, 1993.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on May. 19, 2024