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Intelligent Sensors Technologies for Industry 5.0 and Smart Manufacturing

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

Deadline for manuscript submissions: 20 June 2024 | Viewed by 516

Special Issue Editor


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Guest Editor
Industrial and Management Systems Engineering, West Virginia University, Morgantown, WV 26506, USA
Interests: smart sensors; Industry 5.0; smart manufacturing

Special Issue Information

Dear Colleagues,

Building upon significant developments in Industry 4.0, the next phase in the evolution of smart manufacturing is Industry 5.0. In this domain of Industry 5.0, humans and machines work in an integrated manner to achieve high levels of productivity and efficiency. A more flexible and advanced manufacturing context is addressed by a combination of the strengths of humans and machines, leveraging automation and artificial intelligence to produce a highly productive manufacturing environment. The advancement of the manufacturing industry is enhanced by high levels of automation and data-based technology, thus creating the optimum environment for smart manufacturing. While Industry 4.0 focused primarily on communication and automation, Industry 5.0 brings the skills of humans into alignment with the manufacturing process. High levels of productivity and efficiency can be achieved by combining the strengths of humans and machines within the context of effective data transfer and communication protocols. This integrative synergy between humans and machines allows the manufacturing processes to be more adaptable to suit the needs of production in the context of high levels of quality. Difficult real-time challenges faced in manufacturing and production can be addressed through the unique collaboration of activities planned to be accomplished by humans and machines. The framework of Industry 5.0 requires effective data transfer, information flow, data conversion to knowledge over time, and assessment of production parameters with respect to continuing effectiveness and applicability. Intelligent data-driven sensors and controls thus have a significant role to play in Industry 5.0 as they will be the bearers of information from technical, economic, and procedural aspects, continually monitoring system effectiveness and improvement potential.

Prof. Dr. Bhaskaran Gopalakrishnan
Guest Editor

Manuscript Submission Information

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Keywords

  • advanced manufacturing
  • smart manufacturing
  • intelligent sensors and controls
  • Industry 5.0
  • productivity
  • efficiency

Published Papers (1 paper)

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Review

41 pages, 5837 KiB  
Review
Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review
by Hossein Gohari, Mahmoud Hassan, Bin Shi, Ahmad Sadek, Helmi Attia and Rachid M’Saoubi
Sensors 2024, 24(7), 2324; https://doi.org/10.3390/s24072324 - 05 Apr 2024
Viewed by 343
Abstract
The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing sources of uncertainty and estimating the optimal cutting parameters. [...] Read more.
The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems, with a focus on cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in offline and online process optimization approaches are presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, reduced energy consumption, and carbon emissions are independently investigated for these offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, this paper explores the challenges and opportunities inherent to developing a robust cyber–physical optimization system. Full article
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