Abstract
This study presents a preliminary method to assess and predict the quality of chemically bonded sand molds through the use of embedded sensors. Utilizing miniature hardware, critical variables were measured and used as indicators of curing progression, ultimately predicting the 24-h transverse strength of phenolic-urethane no-bake and furan no-bake sand systems. Employing ANOVA and regression analyses, significant correlations were established between sensor data and strength prediction. This approach, if integrated into production, offers real-time evaluation with the potential to be automated by machine learning. While acknowledging the study’s limitations, this research introduces an innovative strategy for optimizing molding outcomes in the foundry industry through wireless, sensor-based monitoring.
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Acknowledgements
This research is sponsored by the DLA-Troop Support, Philadelphia, PA and the Defense Logistics Agency Information Operations, J68, Research & Development, Ft. Belvoir, VA. The authors wish to acknowledge the efforts of University of Northern Iowa staff member Nico Costleigh and student Claire Kipp for their assistance in conducting the experiments. This paper is based upon a presentation made in the 2024 AFS Metalcasting Congress and will be published in the AFS Transaction Vol. 132 A shortened version was submitted to the FEF-IJMC Research Competition 2023 and presented at the 2023 Metalcasting Congress by the team of Jacob O’Dell and Joshua I. Kowalsky.
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Bryant, N.C., O’Dell, J.L., Kowalsky, J.I. et al. Real-Time Measurement of Mold and Core Quality in Chemically Bonded Sands. Inter Metalcast 18, 14–22 (2024). https://doi.org/10.1007/s40962-023-01206-3
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DOI: https://doi.org/10.1007/s40962-023-01206-3