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Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE
The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348603/ https://www.ncbi.nlm.nih.gov/pubmed/34372316 http://dx.doi.org/10.3390/s21155077 |
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author | Vasilev, Momchil MacLeod, Charles N. Loukas, Charalampos Javadi, Yashar Vithanage, Randika K. W. Lines, David Mohseni, Ehsan Pierce, Stephen Gareth Gachagan, Anthony |
author_facet | Vasilev, Momchil MacLeod, Charles N. Loukas, Charalampos Javadi, Yashar Vithanage, Randika K. W. Lines, David Mohseni, Ehsan Pierce, Stephen Gareth Gachagan, Anthony |
author_sort | Vasilev, Momchil |
collection | PubMed |
description | The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs. |
format | Online Article Text |
id | pubmed-8348603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83486032021-08-08 Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE Vasilev, Momchil MacLeod, Charles N. Loukas, Charalampos Javadi, Yashar Vithanage, Randika K. W. Lines, David Mohseni, Ehsan Pierce, Stephen Gareth Gachagan, Anthony Sensors (Basel) Article The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs. MDPI 2021-07-27 /pmc/articles/PMC8348603/ /pubmed/34372316 http://dx.doi.org/10.3390/s21155077 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vasilev, Momchil MacLeod, Charles N. Loukas, Charalampos Javadi, Yashar Vithanage, Randika K. W. Lines, David Mohseni, Ehsan Pierce, Stephen Gareth Gachagan, Anthony Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title | Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title_full | Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title_fullStr | Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title_full_unstemmed | Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title_short | Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE |
title_sort | sensor-enabled multi-robot system for automated welding and in-process ultrasonic nde |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348603/ https://www.ncbi.nlm.nih.gov/pubmed/34372316 http://dx.doi.org/10.3390/s21155077 |
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