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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...

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Detalles Bibliográficos
Autores principales: Tahir, Muhammad Ashhal, Ramis Ferrer, Borja, Martinez Lastra, Jose Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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.
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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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