Abstract
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.
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