| Title: | Aging in industry 5.0 : enhancing human–robot synergy in manufacturing and logistics |
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| Authors: | ID Ranasinghe, Thilini (Author)
ID Grosse, Eric (Author)
ID Lerher, Tone (Author) |
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| Files: |  RAZ_Ranasinghe_Thilini_2024.pdf (651,28 KB)
MD5: A51C5BF3BB61CEE532E44291EB26FA66
 https://www.sciencedirect.com/science/article/pii/S2405896324016689?via%3Dihub
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.08 - Published Scientific Conference Contribution |
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| Organization: | FL - Faculty of Logistic
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| Abstract: | Thanks to rapid technological developments in robotics, various automation technologies are being applied in warehouses today. Order picking, as a key process in warehouse operations, has drawn attentioThis paper presents a systematic literature review exploring the impact of human–robot (HR) systems on older workers in manufacturing and logistics industries, drawing insights into how these systems can be optimally designed to address human factors in four key areas—perceptual, physical, cognitive, and psychosocial—aligning with the goals of Industry 5.0. By analyzing 19 articles selected from the Scopus and Web of Science databases, we identified both the benefits and challenges that HR systems pose to the aging workforce. We conclude that to achieve Industry 5.0 goals, HR systems must be designed to balance automation with human skills, promoting adaptability and inclusivity tailored to the diverse responses of older workers.n in academia and practice for decades. In addition to many studies dedicated to manual and fully automated order picking, efforts have also been made to study semi-automated warehouses in which humans and robots collaborate. However, these studies mostly focused on system efficiency and ignored ergonomic aspects. Order picking was confirmed as a labor-intensive process in an environment in which workers are at a high risk of developing health problems. Therefore, this study addresses the investigation of physical human working conditions in both manual and robot-assisted order picking systems via real-life laboratory experiments and simulation modeling. We used a motion capture system to assess human working postures when working with and without robot assistance. In addition, we estimated the daily workload by applying the energy expenditure concept. Using simulation experiments, we were able to extend the results to various practical scenarios with different design variables, for example warehouse layouts, order sizes, and human-robot team configuration. Our preliminary results reveal that human-robot collaboration can reduce human workload. Posture evaluation also shows a slight improvement. |
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| Keywords: | aging, human–robot systems, manufacturing, logistics, industry 5.0, human-centricity |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 09.10.2024 |
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| Year of publishing: | 2024 |
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| Number of pages: | Str. 367-372 |
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| Numbering: | issue 19, Vol. 58 |
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| PID: | 20.500.12556/DKUM-91151  |
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| UDC: | 658.5:007.52 |
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| ISSN on article: | 2405-8963 |
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| COBISS.SI-ID: | 215832579 |
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| DOI: | 10.1016/j.ifacol.2024.09.239 |
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| Publication date in DKUM: | 21.11.2024 |
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| Views: | 177 |
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| Downloads: | 53 |
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| Metadata: |    |
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| Categories: | Misc.
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