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Assembly Line Quality Inspection Using Artifical Intelligence Based Computer Vision

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dc.contributor.authorWan Mohd Syakiran Bin Wan Shamshudinen_US
dc.date.accessioned2023-05-03T15:02:20Z
dc.date.available2023-05-03T15:02:20Z
dc.date.issued2019-10
dc.description.abstractThe efficiency of the industrial production line is determined by the rejection rate, the ratio of how much output can be kept and how many needs to be scrapped. Detection of defects along the production line can reduce these wastages before products are delivered to clients. Assembly line quality inspection using Artificial Intelligence based computer vision has been introduced to monitor process quality continuously during the manufacturing process. This project aims to improve Automated Optical Inspection (AOI) systems by using machine vision to detect differences between a finished product and a given reference product. Additionally, a deep learning artificial intelligence neural network will categorize the types of defects that are detected such as scratch, crack, and dent. This project proposes to combine visual inspection with deep learning artificial neural networks to achieve improved detection of production defects on a production line.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/20482
dc.language.isoenen_US
dc.subjectAssembly Line Quality Inspectionen_US
dc.titleAssembly Line Quality Inspection Using Artifical Intelligence Based Computer Visionen_US
dspace.entity.typePublication
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