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Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and <em>operando</em> X-ray radiography guidance
Pandiyan, V., Masinelli, G., Claire, N., Le-Quang, T., Hamidi-Nasab, M., de Formanoir, C., … Wasmer, K. (2022). Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and operando X-ray radiography guidance. Additive Manufacturing, 58, 103007 (15pp.). https://doi.org/10.1016/j.addma.2022.103007
Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process
Pandiyan, V., Drissi-Daoudi, R., Shevchik, S., Masinelli, G., Le-Quang, T., Logé, R., & Wasmer, K. (2022). Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process. Journal of Materials Processing Technology, 303, 117531 (14 pp.). https://doi.org/10.1016/j.jmatprotec.2022.117531
In situ quality monitoring in direct energy deposition process using co-axial process zone imaging and deep contrastive learning
Pandiyan, V., Cui, D., Le-Quang, T., Deshpande, P., Wasmer, K., & Shevchik, S. (2022). In situ quality monitoring in direct energy deposition process using co-axial process zone imaging and deep contrastive learning. Journal of Manufacturing Processes, 81, 1064-1075. https://doi.org/10.1016/j.jmapro.2022.07.033
Energy-efficient laser welding with beam oscillating technique - a parametric study
Le-Quang, T., Faivre, N., Vakili-Farahani, F., & Wasmer, K. (2021). Energy-efficient laser welding with beam oscillating technique - a parametric study. Journal of Cleaner Production, 313, 127796 (11 pp.). https://doi.org/10.1016/j.jclepro.2021.127796
Artificial intelligence for monitoring and control of metal additive manufacturing
Masinelli, G., Shevchik, S. A., Pandiyan, V., Quang-Le, T., & Wasmer, K. (2021). Artificial intelligence for monitoring and control of metal additive manufacturing. In M. Meboldt & C. Klahn (Eds.), Industrializing additive manufacturing. Proceedings of AMPA2020 (pp. 205-220). https://doi.org/10.1007/978-3-030-54334-1_15
Semi-supervised monitoring of laser powder bed fusion process based on acoustic emissions
Pandiyan, V., Drissi-Daoudi, R., Shevchik, S., Masinelli, G., Le-Quang, T., Logé, R., & Wasmer, K. (2021). Semi-supervised monitoring of laser powder bed fusion process based on acoustic emissions. Virtual and Physical Prototyping, 16(4), 481-497. https://doi.org/10.1080/17452759.2021.1966166
Machine learning monitoring for laser osteotomy
Shevchik, S., Nguendon Kenhagho, H., Le-Quang, T., Faivre, N., Meylan, B., Guzman, R., … Wasmer, K. (2021). Machine learning monitoring for laser osteotomy. Journal of Biophotonics, 14(4), e202000352 (11 pp.). https://doi.org/10.1002/jbio.202000352
Investigations of surface defects during laser polishing of tool steel
Meylan, B., Calderon, I., Tri Le, Q., & Wasmer, K. (2020). Investigations of surface defects during laser polishing of tool steel. In M. Schmidt, F. Vollertsen, & E. Govekar (Eds.), Procedia CIRP: Vol. 94. 11th CIRP conference on photonic technologies [LANE 2020] (pp. 942-946). https://doi.org/10.1016/j.procir.2020.09.092
Supervised deep learning for real-time quality monitoring of laser welding with X-ray radiographic guidance
Shevchik, S., Le-Quang, T., Meylan, B., Vakili Farahani, F., Olbinado, M. P., Rack, A., … Wasmer, K. (2020). Supervised deep learning for real-time quality monitoring of laser welding with X-ray radiographic guidance. Scientific Reports, 10, 3389 (12 pp.). https://doi.org/10.1038/s41598-020-60294-x
Sensitivity analysis of acoustic emission detection using fiber bragg gratings with different optical fiber diameters
Violakis, G., Le-Quang, T., Shevchik, S. A., & Wasmer, K. (2020). Sensitivity analysis of acoustic emission detection using fiber bragg gratings with different optical fiber diameters. Sensors, 20(22), 6511 (11 pp.). https://doi.org/10.3390/s20226511
Laser welding quality monitoring via graph support vector machine with data adaptive kernel
Shevchik, S. A., Le-Quang, T., Farahani, F. V., Faivre, N., Meylan, B., Zanoli, S., & Wasmer, K. (2019). Laser welding quality monitoring via graph support vector machine with data adaptive kernel. IEEE Access, 7, 93108-93122. https://doi.org/10.1109/ACCESS.2019.2927661
Piezo acoustic versus opto-acoustic sensors in laser processing
Wasmer, K., Le-Quang, T., Shevchik, S. A., & Violakis, G. (2019). Piezo acoustic versus opto-acoustic sensors in laser processing. In NDT.net (p. (8 pp.).
Why is in situ quality control of laser keyhole welding a real challenge?
Le-Quang, T., Shevchik, S. A., Meylan, B., Vakili-Farahani, F., Olbinado, M. P., Rack, A., & Wasmer, K. (2018). Why is in situ quality control of laser keyhole welding a real challenge? In M. Schmidt, F. Vollertsen, & G. Dearden (Eds.), Procedia CIRP: Vol. 74. 10th CIRP conference on photonic technologies [LANE 2018] (pp. 649-653). https://doi.org/10.1016/j.procir.2018.08.055
Acoustic Emission for <i>in situ</i> monitoring of laser processing
Shevchik, S., Le, Q. T., Meylan, B., & Wasmer, K. (2018). Acoustic Emission for in situ monitoring of laser processing. In Conference proceedings Ewgae 2018 (p. (9 pp.). CETIM.
AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence
Wasmer, K., Le, T. Q., Meylan, B., Vakili-Farahani, F., Leinenbach, C., Olbinado, M. P., … Shevchik, S. A. (2018). AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence. Presented at the ESRF user meeting 2018. Grenoble, France.
Laser processing quality monitoring by combining acoustic emission and machine learning: a high-speed X-ray imaging approach
Wasmer, K., Le-Quang, T., Meylan, B., Vakili-Farahani, F., Olbinado, M. P., Rack, A., & Shevchik, S. A. (2018). Laser processing quality monitoring by combining acoustic emission and machine learning: a high-speed X-ray imaging approach. In M. Schmidt, F. Vollertsen, & G. Dearden (Eds.), Procedia CIRP: Vol. 74. 10th CIRP conference on photonic technologies [LANE 2018] (pp. 654-658). https://doi.org/10.1016/j.procir.2018.08.054
When AE (acoustic emission) meets AI (artificial intelligence) II
Wasmer, K., Saeidi, F., Meylan, B., Le, Q. T., & Shevchik, S. A. (2018). When AE (acoustic emission) meets AI (artificial intelligence) II. In Conference proceedings Ewgae 2018 (p. (12 pp.). CETIM.