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Sensors for Intelligent Manufacturing Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 4721

Special Issue Editor


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Guest Editor
Factory Automation Systems and Technologies Laboratory, Tampere University, 33101 Tampere, Finland
Interests: factory automation; industrial informatics; networked embedded systems; multi agent-based production control; industrial networks (incl. Wireless connectivity)
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Special Issue Information

Dear Colleagues,

In recent years, the world in general, and the industrial world in particular, has been living a revolution. The interconnected society is a reality, bringing new business opportunities and, in theory, a better life for the human race. Within the industrial manufacturing sector, the most desired asset is information capable of supporting run-time intelligence for the optimization of industrial activities. In order to create that information, data needs to be gathered—if possible, close to the source. It is at this point where sensor technology plays a crucial role.

This Special Issue invites submissions targeting the following topics:

  • sensors fundamentals targeting intelligent manufacturing systems;
  • sensors architectures and infrastructures for highly dynamic manufacturing systems;
  • sensors applications for monitoring large manufacturing systems;
  • sensors solutions for self-healing manufacturing assets;
  • energy harvesting mechanisms for industrial wireless sensors;
  • sensors solutions for high-speed robotics systems.

Prof. Dr. Jose L. Martinez Lastra
Guest Editor

Manuscript Submission Information

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Published Papers (1 paper)

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Research

21 pages, 3519 KiB  
Article
An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting
by Muhammad Ashhal Tahir, Borja Ramis Ferrer and Jose Luis Martinez Lastra
Sensors 2019, 19(3), 438; https://doi.org/10.3390/s19030438 - 22 Jan 2019
Cited by 6 | Viewed by 4043
Abstract
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, [...] Read more.
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. Full article
(This article belongs to the Special Issue Sensors for Intelligent Manufacturing Systems)
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