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An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting
The manufacturing industry requests novel solutions that will permit enterprises to stay competitive in the market. This leads to decisions being made based on different technologies that are focused on real-time accurate measurement and monitoring of manufacturing assets. In the context of traceabi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387058/ https://www.ncbi.nlm.nih.gov/pubmed/30678151 http://dx.doi.org/10.3390/s19030438 |
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author | Tahir, Muhammad Ashhal Ramis Ferrer, Borja Martinez Lastra, Jose Luis |
author_facet | Tahir, Muhammad Ashhal Ramis Ferrer, Borja Martinez Lastra, Jose Luis |
author_sort | Tahir, Muhammad Ashhal |
collection | PubMed |
description | The manufacturing industry requests novel solutions that will permit enterprises to stay competitive in the market. This leads to decisions being made based on different technologies that are focused on real-time accurate measurement and monitoring of manufacturing assets. In the context of traceability, radio frequency identification (RFID) tags have been traditionally used for tracking, monitoring, and collecting data of various manufacturing resources operating along the value chain. RFID tags and microelectromechanical systems (MEMS) sensors enable the monitoring of manufacturing assets by providing real-time data. Such devices are usually powered by batteries that need regular maintenance, which in turn leads to delays that affect the overall manufacturing process time. This article presents a low-cost approach to detect and measure radio frequency (RF) signals in assembly lines for optimizing the manufacturing operations in the manufacturing industry. Through the detection and measurement of RF signals, the RF energy can be harvested at certain locations on the assembly line. Then, the harvested energy can be supplied to the MEMS sensors, minimizing the regular maintenance for checking and replacing batteries. This leads to an increase in the operational efficiency and an overall reduction in operational and maintenance costs. |
format | Online Article Text |
id | pubmed-6387058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63870582019-02-26 An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting Tahir, Muhammad Ashhal Ramis Ferrer, Borja Martinez Lastra, Jose Luis Sensors (Basel) Article The manufacturing industry requests novel solutions that will permit enterprises to stay competitive in the market. This leads to decisions being made based on different technologies that are focused on real-time accurate measurement and monitoring of manufacturing assets. In the context of traceability, radio frequency identification (RFID) tags have been traditionally used for tracking, monitoring, and collecting data of various manufacturing resources operating along the value chain. RFID tags and microelectromechanical systems (MEMS) sensors enable the monitoring of manufacturing assets by providing real-time data. Such devices are usually powered by batteries that need regular maintenance, which in turn leads to delays that affect the overall manufacturing process time. This article presents a low-cost approach to detect and measure radio frequency (RF) signals in assembly lines for optimizing the manufacturing operations in the manufacturing industry. Through the detection and measurement of RF signals, the RF energy can be harvested at certain locations on the assembly line. Then, the harvested energy can be supplied to the MEMS sensors, minimizing the regular maintenance for checking and replacing batteries. This leads to an increase in the operational efficiency and an overall reduction in operational and maintenance costs. MDPI 2019-01-22 /pmc/articles/PMC6387058/ /pubmed/30678151 http://dx.doi.org/10.3390/s19030438 Text en © 2019 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 Tahir, Muhammad Ashhal Ramis Ferrer, Borja Martinez Lastra, Jose Luis An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title | An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title_full | An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title_fullStr | An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title_full_unstemmed | An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title_short | An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting |
title_sort | approach for managing manufacturing assets through radio frequency energy harvesting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387058/ https://www.ncbi.nlm.nih.gov/pubmed/30678151 http://dx.doi.org/10.3390/s19030438 |
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