Abstract
Assessing metal cleanliness of aluminum melts is critical for product quality control, as well as for process optimization. PoDFA is the current standard method for assessing aluminum cleanliness but has limitations in speed and costs due to its manual image processing. The Automated Metal Cleanliness Analyzer (AMCA) method was previously demonstrated to produce cleanliness indicators highly correlating to the main cleanliness indicator of industrial PoDFA analyses on the same samples. In the present work, the features of the AMCA method were expanded, introducing quantitative inclusion characterization and enhanced detection features. The results were systematically benchmarked against industrial PoDFA-derived cleanliness data. The results confirm the equivalence of the total particle area and provide moderate differentiation of inclusion types. Thereby, AMCA shows potential to be used as an alternative to PoDFA, deriving cleanliness data of aluminum samples for generating extensive process data at superior cost-scaling and minimized human biases.
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References
‘PoDFA, The complete solution for inclusion measurement, Inclusion identification and quantification analysis’. ABB Inc., 2016. [Online]. Available: https://library.e.abb.com/public/b706913462934969befe277d80880795/PB_PoDFA-EN_A.pdf.
P. V. Evans, P. G. Enright, and R. A. Ricks, ‘Molten Metal Cleanliness: Recent Developments to Improve Measurement Reliability’, in Light Metals 2018, O. Martin, Ed. Cham: Springer International Publishing, 2018, pp. 839–846. https://doi.org/10.1007/978-3-319-72284-9_109.
H. Duval, C. Rivière, É. Laé, P. Le Brun, and J.-B. Guillot, ‘Pilot-Scale Investigation of Liquid Aluminum Filtration through Ceramic Foam Filters: Comparison between Coulter Counter Measurements and Metallographic Analysis of Spent Filters’, Metall. Mater. Trans. B, vol. 40, no. 2, pp. 233–246, Apr. 2009. https://doi.org/10.1007/s11663-008-9222-y.
H. Zedel, R. Fritzsch, S. Akhtar, and R. E. Aune, ‘Automated Metal Cleanliness Analyzer (AMCA)—An Alternative Assessment of Metal Cleanliness in Aluminum Melts’, in Light Metals 2021, L. Perander, Ed. Cham: Springer International Publishing, 2021, pp. 778–784. https://doi.org/10.1007/978-3-030-65396-5_102.
H. Zedel, R. Fritzsch, S. Akhtar, and R. E. Aune, ‘Estimation of Aluminum Melt Filtration Efficiency Using Automated Image Acquisition and Processing’, in Light Metals 2019, C. Chesonis, Ed. Cham: Springer International Publishing, 2019, pp. 1113–1120. https://doi.org/10.1007/978-3-030-05864-7_136.
C. Stanica and P. Moldovan, ‘Aluminium melt cleanliness performance evaluation using PoDFA (Porous Disk Filtration Apparatus) technology’, UPB Sci Bull Ser B, vol. 71, no. 4, 2009, [Online]. Available: https://www.scientificbulletin.upb.ro/rev_docs_arhiva/full6739.pdf.
‘MATLAB’. The MathWorks Inc., Natick, Massachusetts, 2021.
D. Perez Clos, H. Zedel, S. G. Johnsen, P. Nekså, and R. E. Aune, ‘Particle deposition characteristics in the formation of Hard Grey Scale (HGS) on cold surfaces exposed to aluminium production off-gas’, J. Aerosol Sci., vol. 161, p. 105946, Mar. 2022. https://doi.org/10.1016/j.jaerosci.2021.105946.
Acknowledgements
The authors wish to express their gratitude to the Department of Materials Science and Engineering and the Department of Chemistry at the Norwegian University of Science and Technology (NTNU) for their continuous support, to NTNU Technology Transfer AS (NTNU TTO) for their administrative and strategical support of the project, as well as to Norsk Hydro ASA in Karmøy for the provision of PoDFA micrographs and continuous support of the project.
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Zedel, H., Fritzsch, R., Akhtar, S., Aune, R.E. (2023). Automated Metal Cleanliness Analyzer (AMCA): Digital Image Analysis Phase Differentiation and Benchmarking Against PoDFA-Derived Cleanliness Data. In: Broek, S. (eds) Light Metals 2023. TMS 2023. The Minerals, Metals & Materials Series. Springer, Cham. https://doi.org/10.1007/978-3-031-22532-1_117
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DOI: https://doi.org/10.1007/978-3-031-22532-1_117
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