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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/2111
Title: Advanced aerospace component inspection and handling using liquid lenses, machine learning, 3D vision, and robotics
Authors: Tsao En Fu 
Keywords: Aerospace manufacturing;Automated inspection;Machine learning
Issue Date: 2024
Abstract: 
The aerospace industry requires extremely high precision and reliability in the inspection and handling of components, particularly as parts become more complex and miniaturized. Traditional inspection methods are increasingly inadequate, often leading to incomplete quality assessments, higher costs, and potential failures. Recent advances in liquid lenses, machine learning, 3D vision, and robotics offer promising solutions, but their full potential depends on effective integration into a unified system. Liquid lenses enable rapid variable-focus imaging for detailed inspection, while machine learning algorithms improve object recognition, cosmetic defect detection, and optical character recognition with high accuracy. The incorporation of 3D vision enhances spatial awareness for reliable bin picking, and robotics ensures precise and consistent manipulation of components. This research focuses on developing an integrated inspection and handling system that combines these technologies to improve inspection accuracy, reduce processing time, and increase reliability, thereby supporting the aerospace industry’s goals of safety, efficiency, and technological innovation.
URI(1): https://epub.vgu.edu.vn/handle/dlibvgu/2111
Rights: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:Global Production Engineering & Management (GPEM)

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