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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
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
Adaptive laser welding control: a reinforcement learning approach
Masinelli, G., Le-Quang, T., Zanoli, S., Wasmer, K., & Shevchik, S. A. (2020). Adaptive laser welding control: a reinforcement learning approach. IEEE Access, 8, 103803-103814. https://doi.org/10.1109/ACCESS.2020.2998052
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
Re-solidification dynamics and microstructural analysis of laser welded aluminium
Meylan, B., Le-Quang, T., Olbinado, M. P., Rack, A., Shevchik, S. A., & Wasmer, K. (2020). Re-solidification dynamics and microstructural analysis of laser welded aluminium. International Journal of Materials Research, 111(1), 17-22. https://doi.org/10.3139/146.111838
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.