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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Blunt, Liam
University of Huddersfield
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (23/23 displayed)
- 2024Trueness of vat-photopolymerization printing technology of interim fixed partial denture with different building orientationcitations
- 2022Reaction Sintering of Biocompatible Al2O3-hBN Ceramicscitations
- 2020Challenges in Inspecting Internal Features for SLM Additive Manufactured Build Artifactscitations
- 2020The Detection of Unfused Powder in EBM and SLM Additive Manufactured Componentscitations
- 2020Development of an Additive Manufactured Artifact to Characterize Unfused Powder Using Computed Tomographycitations
- 2020Quantification of additive manufacturing induced variations in the global and local performance characteristics of a complex multi-stage control valve trimcitations
- 2019Introduction of a Surface Characterization Parameter Sdrprime for Analysis of Re-entrant Featurescitations
- 2019Hot-melt extrusion process impact on polymer choice of glyburide solid dispersionscitations
- 2019The challenges in edge detection and porosity analysis for dissimilar materials additive manufactured components
- 2018Optimization of surface determination strategies to enhance detection of unfused powder in metal additive manufactured components
- 2018Development of an AM artefact to characterize unfused powder using computer tomography
- 2018Characterisation of powder-filled defects in additive manufactured surfaces using X-ray CT
- 2018An interlaboratory comparison of X-ray computed tomography measurement for texture and dimensional characterisation of additively manufactured partscitations
- 2017Areal surface texture data extraction from X-ray computed tomography reconstructions of metal additively manufactured partscitations
- 2017Results from an interlaboratory comparison of areal surface texture parameter extraction from X-ray computed tomography of additively manufactured parts
- 2017Method for characterizing defects/porosity in additive manufactured components using computer tomography
- 2016Method for Characterization of Material Loss from Modular Head-Stem Taper Surfaces of Hip Replacement Devicescitations
- 2015Implementation of wavelength scanning interferometry for R2R flexible PV barrier films
- 2014Defect Detection in Thin-film Photovoltaics; Towards Improved Efficiency and Longevitycitations
- 2014Development of the basis for in process metrology for roll to roll production of flexible photo voltaics
- 2014An interferometric auto-focusing method for on-line defect assessment on a roll-to-roll process using wavelength scanning interferometry
- 2009Comparison of Type F2 Software Measurement Standards for Surface Texture
- 2006The use of CMM techniques to assess the wear of total knee replacements
Places of action
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document
Method for characterizing defects/porosity in additive manufactured components using computer tomography
Abstract
The key barrier for many industries in adopting additive manufacturing technologies is the lack of quality assurance and repeatability. Defect/porosity analysis is the most important inspection step for any additively manufactured components.<br/>This paper presents a method for the detection of defects/porosity in additive manufactured components using computer tomography. A Nikon XTH225 industrial CT was used to analyse the relative size and location of the defects and assess the capability of the inspection process based on different levels of X-ray detector magnification. To reduce the number of process variables, all the measurement process parameters, such as filament current, acceleration voltage and X-ray filtering material and thickness, are kept constant. The acquired data processing, surface determination process and defect analysis was carried out using the VgStudio Max (Volume Graphics, Germany) software package.<br/>One Ti6AL4V component built using an Arcam Q10 electron beam melting machine (EBM) was used. The results obtained from the XCT scan are compared to the physical defect analysis, by sectioning the component and confirming pore size and location using focus variation interferometry. The effect of surface determination, repeatability and results’ accuracy are discussed. The main focus of the study is on providing best practice regarding the selection of inspection parameters such as magnification to accurately perform the defect detection.