Glue Level Estimation through Automatic Visual Inspection in PCB Manufacturing

Bruno Iglesias, Mario Otani, Felipe Oliveira

2021

Abstract

Nowadays, the increasing use of automatic visual inspection approaches in the manufacturing process is remarkable. The automation of production lines implies profitability and product quality. Moreover, optimized human resources result in process optimization and production increase. This work addresses the problem of optimizing the glue tube replacement in Printed Circuit Boards (PCB) manufacturing, warning a human operator only just in time to replace the glue tube. We propose an approach to estimate the glue level, in the glue injection process, during PCB manufacturing. The proposed methodology is composed of three main steps: i) Pre-Processing; ii) Feature extraction; and iii) Glue level estimation through machine learning. The proposed predictive model learns the relation between visual features and the glue level in the tube. Real and simulated experiments were carried out to validate the proposed approach. Results show the obtained Root Mean Square Error (RMSE) measure of 0.88, using Random Forest regression model. Furthermore, the proposed approach presents high accuracy even regarding noisy images, resulting in RMSE measures of 3.64 and 4.15 for a Salt and Pepper and Gaussian noise, respectively. Experiments demonstrate reliability and robustness, optimizing the manufacturing.

Paper Citation

in Harvard Style

Iglesias B., Otani M. and Oliveira F. (2021). Glue Level Estimation through Automatic Visual Inspection in PCB Manufacturing. In Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-522-7, pages 731-738. DOI: 10.5220/0010540807310738

in Bibtex Style

@conference{icinco21,
author={Bruno Iglesias and Mario Otani and Felipe Oliveira},
title={Glue Level Estimation through Automatic Visual Inspection in PCB Manufacturing},
booktitle={Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2021},
pages={731-738},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010540807310738},
isbn={978-989-758-522-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Glue Level Estimation through Automatic Visual Inspection in PCB Manufacturing
SN - 978-989-758-522-7
AU - Iglesias B.
AU - Otani M.
AU - Oliveira F.
PY - 2021
SP - 731
EP - 738
DO - 10.5220/0010540807310738