Industrial Visual Defect Inspection of Electronic Components with Siamese Neural Network

Warley Barbosa, Lucas Amaral, Tiago Vieira, Bruno Georgevich, Gustavo Melo

2023

Abstract

We present a system focused on the Visual Inspection of Pin Through Hole (PTH) electronic components. The project was developed in a partnership with a multinational Printed Circuit Board Printed Circuit Board (PCB) manufacturing company which requested a solution capable of operating adequately on unseen components, not included in the initial image database used for model training. Traditionally, visual inspection was mostly performed with pre-determined feature engineering which is inadequate for a flexible solution. Hence, we used a one-shot-learning approach based on Siamese Neural Network model trained on anchor-negative-positive triplets. Using a specifically designed web crawler we collected a new and comprehensive database composed of electronic components which is used in extensive experiments for hyperparameters tun-ing on training and validations stages, achieving satisfactory performance. A web application is also presented, which is responsible for the management of operators, recipes, part number, etc. A hardware responsible for attaching the PCBs and a 4K camera is also developed and deployed on industrial environment. The overall system is deployed in a PCB manufacturing plant and its functionality is demonstrated in a relevant scenario, reaching a level 6 in Technology Readiness Level (TRL).

Paper Citation

in Harvard Style

Barbosa W., Amaral L., Vieira T., Georgevich B. and Melo G. (2023). Industrial Visual Defect Inspection of Electronic Components with Siamese Neural Network. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 889-896. DOI: 10.5220/0011696400003417

in Bibtex Style

@conference{visapp23,
author={Warley Barbosa and Lucas Amaral and Tiago Vieira and Bruno Georgevich and Gustavo Melo},
title={Industrial Visual Defect Inspection of Electronic Components with Siamese Neural Network},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={889-896},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011696400003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - Industrial Visual Defect Inspection of Electronic Components with Siamese Neural Network
SN - 978-989-758-634-7
AU - Barbosa W.
AU - Amaral L.
AU - Vieira T.
AU - Georgevich B.
AU - Melo G.
PY - 2023
SP - 889
EP - 896
DO - 10.5220/0011696400003417
PB - SciTePress