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Journal of Intelligent Manufacturing

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27-06-2022

Foreign objects detection using deep learning techniques for graphic card assembly line

Authors: R. J. Kuo, Faisal Fuad Nursyahid

Published in: Journal of Intelligent Manufacturing | Issue 7/2023

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Abstract

An assembly is a process in which operators and machines manufacture products from semi-finished components into finished goods. It is important to conduct quality control at the end of the assembly line and ensure that no foreign object is put on the conveyor. This study uses a case of foreign object detection in graphics card assembly line to create models which is capable of detecting and marking foreign objects using convolutional neural network (CNN) models. This study uses Inception Resnet v2 to conduct the foreign object classification and Attention Residual U-net++ for the foreign object segmentation. Both benchmark datasets and case study dataset are employed for model evaluation. The result shows that the proposed models can have more promising result than some existing models.

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Title: Foreign objects detection using deep learning techniques for graphic card assembly line
Authors: R. J. Kuo
Faisal Fuad Nursyahid
Publication date: 27-06-2022
Publisher: Springer US
Published in: Journal of Intelligent Manufacturing / Issue 7/2023
Print ISSN: 0956-5515
Electronic ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-022-01980-7

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