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Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing

The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In t...

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Detalles Bibliográficos
Autores principales: Korodi, Adrian, Anitei, Denis, Boitor, Alexandru, Silea, Ioan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349585/
https://www.ncbi.nlm.nih.gov/pubmed/32580271
http://dx.doi.org/10.3390/s20123520
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author Korodi, Adrian
Anitei, Denis
Boitor, Alexandru
Silea, Ioan
author_facet Korodi, Adrian
Anitei, Denis
Boitor, Alexandru
Silea, Ioan
author_sort Korodi, Adrian
collection PubMed
description The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive industry, the Electronic Control Unit (ECU) manufacturing ends with complex testing, the End-of-Line (EoL) products being afterwards sent to client companies. This paper proposes an image-processing-based low-cost fault detection (IP-LC-FD) solution for the EoL ECUs, aiming for high-quality and fast detection. The IP-LC-FD solution approaches the problem of determining, on the manufacturing line, the correct mounting of the pins in the locations of each connector of the ECU module, respectively, other defects as missing or extra pins, damaged clips, or surface cracks. The IP-LC-FD system is a hardware–software structure, based on Raspberry Pi microcomputers, Pi cameras, respectively, Python and OpenCV environments. This paper presents the two main stages of the research, the experimental model, and the prototype. The rapid integration into the production line represented an important goal, meaning the accomplishment of the specific hard acceptance requirements regarding both performance and functionality. The solution was implemented and tested as an experimental model and prototype in a real industrial environment, proving excellent results.
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spelling pubmed-73495852020-07-14 Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing Korodi, Adrian Anitei, Denis Boitor, Alexandru Silea, Ioan Sensors (Basel) Article The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive industry, the Electronic Control Unit (ECU) manufacturing ends with complex testing, the End-of-Line (EoL) products being afterwards sent to client companies. This paper proposes an image-processing-based low-cost fault detection (IP-LC-FD) solution for the EoL ECUs, aiming for high-quality and fast detection. The IP-LC-FD solution approaches the problem of determining, on the manufacturing line, the correct mounting of the pins in the locations of each connector of the ECU module, respectively, other defects as missing or extra pins, damaged clips, or surface cracks. The IP-LC-FD system is a hardware–software structure, based on Raspberry Pi microcomputers, Pi cameras, respectively, Python and OpenCV environments. This paper presents the two main stages of the research, the experimental model, and the prototype. The rapid integration into the production line represented an important goal, meaning the accomplishment of the specific hard acceptance requirements regarding both performance and functionality. The solution was implemented and tested as an experimental model and prototype in a real industrial environment, proving excellent results. MDPI 2020-06-22 /pmc/articles/PMC7349585/ /pubmed/32580271 http://dx.doi.org/10.3390/s20123520 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Korodi, Adrian
Anitei, Denis
Boitor, Alexandru
Silea, Ioan
Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title_full Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title_fullStr Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title_full_unstemmed Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title_short Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
title_sort image-processing-based low-cost fault detection solution for end-of-line ecus in automotive manufacturing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349585/
https://www.ncbi.nlm.nih.gov/pubmed/32580271
http://dx.doi.org/10.3390/s20123520
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