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TOWARDS REMOTE CONTROL OF MANUFACTURING MACHINES THROUGH ROBOT VISION SENSORS

Published online by Cambridge University Press:  19 June 2023

Nourhan Halawi Ghoson ,
Nisar Hakam ,
Zohreh Shakeri ,
Vincent Meyrueis ,
Stéphane Loubère  and
Khaled Benfriha
Nourhan Halawi Ghoson*
Affiliation:
Arts et métiers - science et technologie;
Nisar Hakam
Affiliation:
Arts et métiers - science et technologie;
Zohreh Shakeri
Affiliation:
Arts et métiers - science et technologie;
Vincent Meyrueis
Affiliation:
Arts et métiers - science et technologie;
Stéphane Loubère
Affiliation:
PwC | Strategy&
Khaled Benfriha
Affiliation:
Arts et métiers - science et technologie;
*
Halawi Ghoson, Nourhan, Arts et métiers - science et technologie, Lebanon (Lebanese Republic), nourhan.halawi_ghoson@ensam.eu

Abstract

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The remote management of equipment is part of the functionalities granted by the design principles of Industry 4.0. However, some critical operations are managed by operators, machine setup and initialization serve as a significant illustration. Since the initialization is a repetitive task, industrial robots with a smart vision system can undertake these duties, enhancing the autonomy and flexibility of the manufacturing process. The smart vision system is considered essential for the implementation of several characteristics of Industry 4.0. This paper introduces a novel solution for controlling manufacturing machines using an embedded camera on the robot. This implementation requires the development of an interactive interface, designed in accordance with the supervision system known as Manufacturing Execution System. The framework is implemented inside a manufacturing cell, demonstrating a quick response time and an improvement between the cameras.

Keywords

Design engineeringDesign for Additive Manufacturing (DfAM)Design processIndustrial robotsSmart vision sensors
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3601 - 3610
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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