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Human-Centred Smart Manufacturing - Industry 5.0
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Human-Centred Smart Manufacturing - Industry 5.0

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 7100

Special Issue Editors

Prof. Dr. Jorn Mehnen

E-Mail Website
Guest Editor
Design, Manufacturing and Engineering Management Department, The University of Strathclyde, Glasgow G1 1XJ, UK
Interests: Industry 4.0; IoT; AI/CI; big data analysis; cloud manufacturing
Special Issues, Collections and Topics in MDPI journals
Dr. Nikolaos Tapoglou

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, School of Engineering, International Hellenic University, Sindos Campus, 57400 Thessaloniki, Greece
Interests: manufacturing and processing; manufacturing simulation; cloud manufacturing; machine tools; gear manufacturing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jonathan Corney

E-Mail Website
Guest Editor
Digital Manufacturing School of Engineering, University of Edinburgh, Edinburgh, UK
Interests: UWB sensors (for movement of materials and people); Wifi Sensor Networks (in electrically noise production environments); ambient noise sensor (in manufacturing environments); air quality (CO2, NOx, O3) (H&S and Net Zero monitoring); industrial sensor data mining and management; linking realtime activity sensors with digital twins

Special Issue Information

Dear Colleagues,

Implementing Industry 4.0 in a business does not only require excellent science and technology, but it is becoming increasingly evident that we need to adopt a more comprehensive strategy that encompasses enabling technologies such as AI, IIoT, AM, AR/VR/XR, cloud manufacturing, and quantum ML, as well as matching business and sustainability strategies that can be accepted and trusted by people. This broader and human-centered approach is often called Industry 5.0.

This Special Issue has been developed following an interdisciplinary approach to address this broader challenge. It invites scientific articles to contribute to new knowledge through technical and sociotechnical contributions that help academia and industry to establish a more holistic approach to digital technologies. This Special Issue welcomes contributions concerning, e.g., human-centric manufacturing systems, human-in-the-loop control, human–robot collaboration, smart decision-making support, human digital twin, trust, reliability, upgrading and upskilling, as well as human–machine interfaces and sustainable smart manufacturing.

Prof. Dr. Jorn Mehnen
Dr. Nikolaos Tapoglou
Prof. Dr. Jonathan Corney
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human-centric manufacturing systems
  • human-in-the-loop control
  • human–robot collaboration
  • smart decision-making support
  • human digital twin, trust, reliability, upgrading and upskilling
  • human–machine interfaces
  • sustainable smart manufacturing

Published Papers (3 papers)

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Research

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20 pages, 787 KiB  
Article
Using Worker Position Data for Human-Driven Decision Support in Labour-Intensive Manufacturing
by Ayse Aslan, Hanane El-Raoui, Jack Hanson, Gokula Vasantha, John Quigley, Jonathan Corney and Andrew Sherlock
Sensors 2023, 23(10), 4928; https://doi.org/10.3390/s23104928 - 20 May 2023
Viewed by 1204
Abstract
This paper provides a novel methodology for human-driven decision support for capacity allocation in labour-intensive manufacturing systems. In such systems (where output depends solely on human labour) it is essential that any changes aimed at improving productivity are informed by the workers’ actual [...] Read more.
This paper provides a novel methodology for human-driven decision support for capacity allocation in labour-intensive manufacturing systems. In such systems (where output depends solely on human labour) it is essential that any changes aimed at improving productivity are informed by the workers’ actual working practices, rather than attempting to implement strategies based on an idealised representation of a theoretical production process. This paper reports how worker position data (obtained by localisation sensors) can be used as input to process mining algorithms to generate a data-driven process model to understand how manufacturing tasks are actually performed and how this model can then be used to build a discrete event simulation to investigate the performance of capacity allocation adjustments made to the original working practice observed in the data. The proposed methodology is demonstrated using a real-world dataset generated by a manual assembly line involving six workers performing six manufacturing tasks. It is found that, with small capacity adjustments, one can reduce the completion time by 7% (i.e., without requiring any additional workers), and with an additional worker a 16% reduction in completion time can be achieved by increasing the capacity of the bottleneck tasks which take relatively longer time than others. Full article
(This article belongs to the Special Issue Human-Centred Smart Manufacturing - Industry 5.0)
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Review

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25 pages, 1991 KiB  
Review
Industry 5 and the Human in Human-Centric Manufacturing
by Kendra Briken, Jed Moore, Dora Scholarios, Emily Rose and Andrew Sherlock
Sensors 2023, 23(14), 6416; https://doi.org/10.3390/s23146416 - 14 Jul 2023
Cited by 3 | Viewed by 1724
Abstract
Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing which promised a new level of interconnectedness between a diverse range of technologies. Sensors, as a point technology, play an important role in these developments, facilitating human–machine interaction and enabling [...] Read more.
Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing which promised a new level of interconnectedness between a diverse range of technologies. Sensors, as a point technology, play an important role in these developments, facilitating human–machine interaction and enabling data collection for system-level technologies. Concerns for human labour working in I4 environments (e.g., health and safety, data generation and extraction) are acknowledged by Industry 5 (I5), an update of I4 which promises greater attention to human–machine relations through a values-driven approach to collaboration and co-design. This article explores how engineering experts integrate values promoted by policy-makers into both their thinking about the human in their work and in their writing. This paper demonstrates a novel interdisciplinary approach in which an awareness of different disciplinary epistemic values associated with humans and work guides a systematic literature review and interpretive coding of practice-focussed engineering papers. Findings demonstrate evidence of an I5 human-centric approach: a high value for employees as “end-users” of innovative systems in manufacturing; and an increase in output addressing human activity in modelling and the technologies available to address this concern. However, epistemic publishing practices show that efforts to increase the effectiveness of manufacturing systems often neglect worker voice. Full article
(This article belongs to the Special Issue Human-Centred Smart Manufacturing - Industry 5.0)
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22 pages, 2419 KiB  
Review
An Extended AI-Experience: Industry 5.0 in Creative Product Innovation
by Amy Grech, Jörn Mehnen and Andrew Wodehouse
Sensors 2023, 23(6), 3009; https://doi.org/10.3390/s23063009 - 10 Mar 2023
Cited by 5 | Viewed by 3222
Abstract
Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this research to assist and augment creative scenarios in the [...] Read more.
Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this research to assist and augment creative scenarios in the engineering field. A bibliographic analysis is performed to review relevant fields and their relationships. This is followed by a review of current challenges in group ideation and state-of-the-art technologies with the aim of addressing them in this study. This knowledge is applied to the transformation of current ideation scenarios into a virtual environment using AI. The aim is to augment designers’ creative experiences, a core value of Industry 5.0 that focuses on human-centricity, social and ecological benefits. For the first time, this research reclaims brainstorming as a challenging and inspiring activity where participants are fully engaged through a combination of AI and VR technologies. This activity is enhanced through three key areas: facilitation, stimulation, and immersion. These areas are integrated through intelligent team moderation, enhanced communication techniques, and access to multi-sensory stimuli during the collaborative creative process, therefore providing a platform for future research into Industry 5.0 and smart product development. Full article
(This article belongs to the Special Issue Human-Centred Smart Manufacturing - Industry 5.0)
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