Advanced Computer Vision and AI Techniques for Nano-Scale Quality Control in Manufacturing In the Space Industry
DOI:
https://doi.org/10.58445/rars.635Keywords:
Computer Vision, AI , space industryAbstract
This paper examines the integration of advanced computer vision (CV) techniques and Artificial Intelligence (AI) algorithms to improve quality control (QC) for nano-scale manufacturing processes in the space industry. As nanotechnology is regularly used in the space industry for manufacturing electromechanical components such as NEMS (Nanoelectromechanical Systems), solar panels, and energy storage devices, it's becoming increasingly important to detect defects or imperfections in one of those systems to prevent the loss of life and a costly catastrophe. In order to help mediate this issue, this paper will discuss the methods and processes that can be implemented to capture and analyze nano-scale images and data in order to detect possible flaws in the components.
References
admin. (2022, February 14). Quality Management in Aerospace Industry: Things to Know. Compliancehelp Consulting, LLC. https://www.quality-assurance.com/blog/quality-management-in-aerospace-industry-what-you-need-to-know.html
Akundi, A., & Reyna, M. (2021, June 10). A Machine Vision Based Automated Quality Control System for Product Dimensional Analysis. ScienceDirect. https://www.sciencedirect.com/science/article/pii/S1877050921010942
Fahle, S., Prinz, C., & Kuhlenkötter, B. (2020). Systematic review on machine learning (ML) methods for manufacturing processes–Identifying artificial intelligence (AI) methods for field application. Procedia CIRP, 93, 413-418.
Greenfield, D. (n.d.). How Artificial Intelligence Works in Quality Control. Automation World. Retrieved October 8, 2023, from https://www.automationworld.com/factory/sensors/article/21198005/how-artificial-intelligence-works-in-quality-control
Holler, M., Odstrcil, M., Guizar-Sicairos, M. et al. Three-dimensional imaging of integrated circuits with macro- to nanoscale zoom. Nat Electron 2, 464–470 (2019). https://doi.org/10.1038/s41928-019-0309-z
How to Use AI for Quality Control in Manufacturing. (n.d.). Engineering.Com. Retrieved October 8, 2023, from https://www.engineering.com/story/how-to-use-ai-for-quality-control-in-manufacturing
https://www.smartly.cz, S.-. (2021, September 29). Automated nanoscale quality control for reliable, artifact-free atomic force microscopy. TESCAN. https://www.tescan.com/automated-nanoscale-quality-control-for-reliable-artifact-free-atomic-force-microscopy/
Lichtman, J. W., & Conchello, J. A. (2005). Fluorescence microscopy. Nature methods, 2(12), 910-919.
Lopes, M. G., Recktenwald, S. M., Simionato, G., Eichler, H., Wagner, C., Quint, S., & Kaestner, L. (2023). Big data in transfusion medicine and artificial intelligence analysis for red blood cell quality control. Transfusion Medicine and Hemotherapy, 50(3), 163-173.
Mohammed, A., & Abdullah, A. (2018, November). Scanning electron microscopy (SEM): A review. In Proceedings of the 2018 International Conference on Hydraulics and Pneumatics—HERVEX, Băile Govora, Romania (Vol. 2018, pp. 7-9).
Murphy, R. R. (2019). Introduction to AI robotics. MIT press.
Replication and dimensional quality control of industrial nanoscale surfaces using calibrated AFM measurements and SEM image processing. (n.d.). CIRP Annals, 59(1), 563–568. https://doi.org/10.1016/j.cirp.2010.03.141
Silva, R. L., Rudek, M., Szejka, A. L., & Junior, O. C. (2018). Machine vision systems for industrial quality control inspections. In Product Lifecycle Management to Support Industry 4.0: 15th IFIP WG 5.1 International Conference, PLM 2018, Turin, Italy, July 2-4, 2018, Proceedings 15 (pp. 631-641). Springer International Publishing.
The quality control and non-destructive evaluation of composite aerospace components. (n.d.). Composites, 14(2), 115–128. https://doi.org/10.1016/S0010-4361(83)80007-X
Zhou, W., Apkarian, R., Wang, Z. L., & Joy, D. (2007). Fundamentals of scanning electron microscopy (SEM). Scanning Microscopy for Nanotechnology: Techniques and Applications, 1-40.42
Downloads
Posted
Categories
License
Copyright (c) 2023 Gihyun Kim
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.