White Papers
Performance of Eddy Currents for the in-situ detection of defects during metal AM PBF-L
Author:
Jonatan Wicht
Alain Berthoud
Bernard Revaz
AMiquam SA, CH 1196 Gland, Switzerland
Harald Krauss
EOS GmbH Electro Optical Systems, D 82152 Krailling, Germany
Frank Widulle
Carl Zeiss AG, Carl-Zeiss-Str. 22, 73447 Oberkochen, Germany
Julian Schulz
Edson Costa Santos
Carl Zeiss Industrielle Messtechnik GmbH, Carl Zeiss-Str. 22, 73447 Oberkochen, Germany
Notes (Erratum): The units of pore size in Table 1-A is in micrometer (and not mm)
Academic Papers (AMiquam and Partners)
Influence of part temperature on in-situ monitoring of powder bed fusion of metals using eddy current testing
10 April 2024
This paper describes and analyses the impact of the temperature on the in-situ eddy current measurements during PBF-LB manufacturing. The research has been conducted by AMiquam, ETHZ, and inspire in partnership supported by Innosuisse.
In a nutshell: yes, as expected, temperature affects the eddy current response because of the change in the electrical conductivity of the measured part, this is just physics. But, good news, this effect is small compared to that of the defects that matter for production (thanks to the low dependence of the electrical conductivity with temperature in alloys) and, most importantly, it can be taken into account either by IR imaging or by numerical simulation.
Authors: Marvin A. Spurek, Adriaan B. Spierings, Marc Lany, Bernard Revaz, Gilles Santi, Jonatan Wicht & Konrad Wegener
DOI: https://doi.org/10.1007/s40964-024-00600-5
In-Situ Monitoring of Selective Laser Melted Ti–6Al–4V Parts Using Eddy Current Testing and Machine Learning
04 November 2023
The present empirical approach is achieved by setting up trained AI algorithms for the in-situ detection of porosity defects generated during the part fabrication. The algorithms are fed with data collected layer by layer using a specific experimental set up composed of an ECT system mounted on the machine recoater of the SLM machine. The proposed framework which allows the prediction of porosity defects layer by layer with a mean absolute error (MAE) of 0.1% for CNN2D algorithm and 0.11% for LSTM one.
Authors: Haifa Sallem, Hatem Ghorbel, Edouard Goffinet, Adeline Cinna, Jean Pralong, Jonatan Wicht & Bernard Revaz
DOI: https://doi.org/10.1007/978-3-031-47784-3_18
In-situ monitoring of powder bed fusion of metals using eddy current testing
29 October 2022
Powder bed fusion of metals (PBF-LB/M) is the most commonly used additive manufacturing process for the layerwise production of metal parts. Although the technology has developed rapidly in recent years, manufactured parts still lack consistent quality primarily owing to process-inherent variability, and the lack of effective sensing technologies enabling the ability to control the process during part production.
Authors: Marvin A. Spurek, Adriaan B. Spierings, Marc Lany, Bernard Revaz, Gilles Santi, Jonatan Wicht & Konrad Wegener
DOI: https://doi.org/10.1016/j.addma.2022.103259
Relative Density Measurement of PBF-Manufactured 316L and AlSi10Mg Samples via Eddy Current Testing
26 August 2021
Authors: Spurek, M.A.; Luong, V.H.; Spierings, A.B.; Lany, M.; Santi, G.; Revaz, B.; Wegener
DOI: https://doi.org/10.3390/met11091376