Development of an AM artefact to characterize unfused powder using computer tomography

Additive manufacturing (AM) is recognized as a core technology for producing high value components. Producing complex and individually modified components as well as prototypes gives additive manufacturing a substantial advantage over conventional subtractive machining. One of the current barriers for most industries in implementing AM is the lack of build repeatability and a deficit in 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. Detecting unfused powder in AM parts using computer tomography is a challenge because the detection relies on differences in density.
This paper presents an optimized methodology for differentiating between unfused powder and voids in additive manufactured components using computer tomography. Detecting the unfused powder requires detecting the cavities between particles, from previous work it was found that detecting unfused powder requires voxel size as small as 4µm3. For most applications scanning with small voxel size is not reasonable; due to part size, long scan time and data analysis. In this investigation different voxel size used to compare the time for scan and data analysis showing the impact of voxel size on micro defects detection. The powder used was Ti6AL4V with a grain size of 45-100µm, typically employed by Arcam electron beam melting (EBM) machines. The artefact consisted of a 6mm round bar with designed internal features ranging from 50µm to 1400µm that contain a mixture of voids and unfused powder. The diameter and depth of defects were characterised using focus variation microscope then scanned with A Nikon XTH 225 industrial CT was used to measure the artefacts and characterise the internal features for defects/pores.
To reduce the number of process variables, the measurement parameters, such as filament current, acceleration voltage and X-ray filtering material and thickness are kept constant. VgStudio Max 3.0(Volume Graphics, Germany) software package was used for data processing, surface determination and defects/ porosity analysis. The main focus of the study is exploring the optimum methods to enhance the detection capability of pores/defects whilst at the same time minimising the time taken for scan, data analysis and effects of noise on the analysis.