| Title: | Personalizing human–robot workplace parameters in human-centered manufacturing |
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| Authors: | ID Ojsteršek, Robert (Author)
ID Buchmeister, Borut (Author)
ID Javernik, Aljaž (Author) |
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| Files: |  machines-12-00546-v2.pdf (5,12 MB)
MD5: 05CEEA53031A74050FC78B5A7FD65AFC
 https://www.mdpi.com/2075-1702/12/8/546
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | This study investigates the relationship between collaborative robot (CR) parameters and worker utilization and system performance in human–robot collaboration (HRC) environments. We investigated whether optimized parameters increase workplace efficiency and whether adapting these parameters to the individual worker improves workplace outcomes. Three experimental scenarios with different CR parameters were analyzed in terms of the setup time, assembly time, finished products, work in process, and worker utilization. The main results show that personalized CR parameters significantly improve efficiency and productivity. The scenario in which CR parameters were tailored to individual workers, balanced the workload, and minimized worker stress, resulting in higher productivity compared to non-people-centric settings. The study shows that personalization reduces cognitive and physical stress, promotes worker well-being, and is consistent with the principles of human-centered manufacturing. Overall, our research supports the adoption of personalized, collaborative workplace parameters, supported by the mathematical model, to optimize employee efficiency and health, contributing to human-centered and efficient HRC environments. |
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| Keywords: | human–robot workplace, collaborative workplace, human-centered manufacturing, stress index, modelling, efficiencxy |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 08.07.2024 |
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| Article acceptance date: | 09.08.2024 |
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| Publication date: | 11.08.2024 |
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| Publisher: | MDPI |
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| Year of publishing: | 2024 |
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| Number of pages: | 16 str. |
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| Numbering: | Vol. 12, iss. 8, [article no.] 546 |
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| PID: | 20.500.12556/DKUM-90423  |
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| UDC: | 658.5 |
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| ISSN on article: | 2075-1702 |
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| COBISS.SI-ID: | 204299779 |
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| DOI: | 10.3390/machines12080546 |
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| Copyright: | © 2024 by the authors |
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| Publication date in DKUM: | 03.09.2024 |
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| Views: | 207 |
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| Downloads: | 37 |
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| Metadata: |    |
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| Categories: | Misc.
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