Real-time automatic optical system to assists operators in the assembling of electronic components

Autores: Marco Ojer de Andrés Ismael Serrano Fátima Saiz Álvaro Iñigo Barandiaran Martirena Iñaki Gil Daniel Aguinaga David Alejandro

Fecha: 18.03.2020

International Journal of Advanced Manufacturing Technology


Abstract

This work presents an optical inspection-guiding system for electronic board manufacturing. The system monitors in real time the mounting process of electronic components performed by an operator. It visually guides the operator through the mounting process while checking the correctness of its actions. As a consequence, mounting errors are reduced while operator comfort is enhanced. This work also introduces a novel method to generate virtual images from a few real images in order to generate enough data for model training. The proposed method is tested using 7 different descriptor combinations and 4 different classifiers. We have also collected, generated, and evaluated a component dataset of 20 different components, called ECAD. The solution was tested with 16 real scenarios, different electronic boards which are empty or full with components. Finally, a usability test was carried out with 21 different people comparing the original and proposed solutions. The propose system is advantageous since it enhances operator’s comfort and satisfaction, increases mounting speed, and reduces error ratio.

BIB_text

@Article {
title = {Real-time automatic optical system to assists operators in the assembling of electronic components},
journal = {International Journal of Advanced Manufacturing Technology},
pages = {2261-2275},
volume = {107},
keywds = {
Quality control, Computer vision, Machine learning, Electronic manufacturing
}
abstract = {

This work presents an optical inspection-guiding system for electronic board manufacturing. The system monitors in real time the mounting process of electronic components performed by an operator. It visually guides the operator through the mounting process while checking the correctness of its actions. As a consequence, mounting errors are reduced while operator comfort is enhanced. This work also introduces a novel method to generate virtual images from a few real images in order to generate enough data for model training. The proposed method is tested using 7 different descriptor combinations and 4 different classifiers. We have also collected, generated, and evaluated a component dataset of 20 different components, called ECAD. The solution was tested with 16 real scenarios, different electronic boards which are empty or full with components. Finally, a usability test was carried out with 21 different people comparing the original and proposed solutions. The propose system is advantageous since it enhances operator’s comfort and satisfaction, increases mounting speed, and reduces error ratio.


}
doi = {10.1007/s00170-020-05125-z},
date = {2020-03-18},
}
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