Tavana, M., Kazemi, M.R., Vafadarnikjoo, A. orcid.org/0000-0003-2147-6043 et al. (1 more author) (2016) An artificial immune algorithm for ergonomic product classification using anthropometric measurements. Measurement: Journal of the International Measurement Confederation, 94. pp. 621-629. ISSN 0263-2241
Abstract
Product classification using anthropometric measurements leads to ergonomic product design and user satisfaction. We propose an effective artificial immune algorithm (AIA) to classify ergonomic products with multi-criteria anthropometric measurements and tune the AIA parameters with a full factorial experimental design approach. We demonstrate the applicability and efficacy of the proposed algorithm by considering the anthropometric measurements of the hand, developing an ergonomic computer mouse, and classifying consumers into three categories. The resulting classifications are compared with expert opinions to facilitate the conformity of the computer mouse to user requirements.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Elsevier Ltd. This is an author produced version of a paper subsequently published in Measurement. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Ergonomic product classification; Anthropometric measurements; Artificial immune algorithm; Ergonomic product design; Meta-heuristic |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Jan 2022 08:16 |
Last Modified: | 25 Jan 2022 09:37 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.measurement.2016.09.007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182838 |