Oyekan, J., Hutabarat, W. orcid.org/0000-0001-7393-7695, Turner, C. et al. (2 more authors) (2020) Using Therbligs to embed intelligence in workpieces for digital assistive assembly. Journal of Ambient Intelligence and Humanized Computing, 11 (6). pp. 2489-2503. ISSN 1868-5137
Abstract
Current OEM (Original Equipment Manufacturer) facilities tend to be highly integrated and are often situated on one site. While providing scale of production such centralisation may create barriers to the achievement of fully flexible, adaptable, and reconfigurable factories. The advent of Industry 4.0 opens up opportunities to address these barriers by decentralising information and decision-making in manufacturing systems through CPS (Cyber Physical Systems) use. This research presents a qualitative study that investigates the possibility of distributing information and decision-making logic into ‘smart workpieces’ which can actively participate in assembly operations. To validate the concept, a use-case demonstrator, corresponding to the assembly of a ‘flat-pack’ table, was explored. Assembly parts in the demonstrator, were equipped with computation, networking, and interaction capabilities. Ten participants were invited to evaluate the smart assembly method and compare its results to the traditional assembly method. The results showed that in its current configuration the smart assembly was slower. However, it made the assembly process more flexible, adaptable and reconfigurable.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | Smart workpiece; Smart factory; Industry 4.0; Assembly operation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number Royal Academy of Engineering (The) N/A |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Jul 2019 08:46 |
Last Modified: | 07 Dec 2021 09:17 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1007/s12652-019-01294-2 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147259 |
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