Browsing by Author "Alsubaei, Obaid Fadghosh"

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Exploring the Potential of Thermographic Data and Machine Learning for Defect Detection in Automated Fiber Placement (AFP)
(University of Strathclyde, 2024-02-06) Alsubaei, Obaid Fadghosh; Yang, Erfu
(Part1) The increasing demand for composites in the industry has led to the development of new automated manufacturing techniques such as Automated Fiber Placement (AFP). However, owing to some factors, small defects can occur during the AFP process which may compromise the structural integrity of the product. Traditionally these defects are detected manually by inaccurate and time-consuming inspection methods. In order to resolve this problem, it is necessary to implement effective automated defect detection systems. As an attempt to contribute to the solution of the problem, this paper reviews the current state of automated defect detection in AFP, and explores the potential of machine learning for improving defect detection. The review provides background information on composite materials, traditional and automated composite manufacturing methods, and defects associated with AFP. It also discusses traditional inspection techniques used in AFP and existing techniques for automated defect detection, in particular machine learning-based techniques. In addition, it also covers different data acquisition approaches for training ML algorithms. The paper aims to contribute towards advancing automated defect detection in AFP by utilizing machine learning techniques coupled with thermographic datasets in order to offer fast, accurate and cost-effective defect detection methods.
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