An artificial immune algorithm for ergonomic product classification using anthropometric measurements

Tavana, M, Kazemi, MR, Vafadarnikjoo, A ORCID: https://orcid.org/0000-0003-2147-6043 and Mobin, M (2016) An artificial immune algorithm for ergonomic product classification using anthropometric measurements. Measurement, 94. pp. 621-629. ISSN 0263-2241

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Official URL: https://doi.org/10.1016/j.measurement.2016.09.007

Abstract

© 2016 Elsevier Ltd 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.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	13 May 2021 11:33
Publisher:	Elsevier
Divisions:	Faculties > Business and Law
Subject terms:	Science & Technology, Technology, Engineering, Multidisciplinary, Instruments & Instrumentation, Engineering, Ergonomic product classification, Anthropometric measurements, Artificial immune algorithm, Ergonomic product design, Meta-heuristic, SUPPORT VECTOR MACHINE, HAND ANTHROPOMETRY, COMPUTER MOUSE, FEATURE-SELECTION, NEURAL-NETWORK, DESIGN, SYSTEM, POSTURE, TASK, Electrical & Electronic Engineering, 0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 0913 Mechanical Engineering
URI:	https://mmu-uat.leaf.cosector.com/id/eprint/627673
DOI:	https://doi.org/10.1016/j.measurement.2016.09.007
ISSN	0263-2241

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