Manufacturing technologies deliver products that can suffer from various defects, one of which is internal porosity. Pores are present in most of the parts produced by, e.g., casting, additive manufacturing, and injection molding and can significantly affect the performance of the final products. Due to technological and economic limits, typically porosity cannot be completely removed by optimizing process parameters. It is therefore essential to have a measurement technique that can detect and evaluate these defects accurately. Apart from conventional nondestructive techniques, such as ultrasonic testing or Archimedes’ method that suffer from various limitations, X-ray computed tomography has emerged as a promising solution capable of measuring size, spatial distribution, and shape of pores. In this paper, a method to achieve traceable computed tomography measurements of internal porosity using a reference object with calibrated internal artificial defects is described and demonstrated on an industrial case study. Furthermore, the possibility to improve measurement results by optimizing parameters used for the evaluation of acquired data is discussed. The optimization method is based on an iterative procedure that reduces to ±5 × 10−5 mm3 the error of the measured values of total void content in the reference object.
Skip Nav Destination
Article navigation
Research-Article
Traceable Porosity Measurements in Industrial Components Using X-Ray Computed Tomography
Petr Hermanek,
Petr Hermanek
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: petr.hermanek@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: petr.hermanek@unipd.it
Search for other works by this author on:
Filippo Zanini,
Filippo Zanini
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: filippo.zanini@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: filippo.zanini@unipd.it
Search for other works by this author on:
Simone Carmignato
Simone Carmignato
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: simone.carmignato@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: simone.carmignato@unipd.it
Search for other works by this author on:
Petr Hermanek
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: petr.hermanek@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: petr.hermanek@unipd.it
Filippo Zanini
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: filippo.zanini@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: filippo.zanini@unipd.it
Simone Carmignato
Department of Management and Engineering,
Stradella San Nicola 3, 36100 Vicenza,
e-mail: simone.carmignato@unipd.it
University of Padova
,Stradella San Nicola 3, 36100 Vicenza,
Italy
e-mail: simone.carmignato@unipd.it
Manuscript received September 5, 2017; final manuscript received March 1, 2019; published online March 28, 2019. Assoc. Editor: Dragan Djurdjanovic.
J. Manuf. Sci. Eng. May 2019, 141(5): 051004 (8 pages)
Published Online: March 28, 2019
Article history
Received:
September 5, 2017
Revision Received:
March 1, 2019
Accepted:
March 1, 2019
Citation
Hermanek, P., Zanini, F., and Carmignato, S. (March 28, 2019). "Traceable Porosity Measurements in Industrial Components Using X-Ray Computed Tomography." ASME. J. Manuf. Sci. Eng. May 2019; 141(5): 051004. https://doi.org/10.1115/1.4043192
Download citation file:
Get Email Alerts
Related Articles
Computed Tomography Artifact Reduction Employing a Convolutional Neural Network Within the Context of Dimensional Metrology
ASME J Nondestructive Evaluation (February,2024)
Pore Formation in Laser-Assisted Powder Deposition Process
J. Manuf. Sci. Eng (October,2009)
Very Low-Intensity Throughput X-Ray Computed Tomography of a Cast FeMnAl Steel Alloy
ASME J Nondestructive Evaluation (November,2020)
Toward Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science
J. Manuf. Sci. Eng (July,2021)
Related Proceedings Papers
Related Chapters
Application of Adaptive Grayscale Morphological Operators for Image Analysis
Intelligent Engineering Systems through Artificial Neural Networks Volume 18
Application and Study on QR-Based Least-Squares Method Algorithm in Concrete Ultrasonic Computerized Tomography
International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)
X-ray Computed Tomography of Cavitating Flow in a Converging-Diverging Nozzle
Proceedings of the 10th International Symposium on Cavitation (CAV2018)