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Article
No TitleAn Artificial Immune Algorithm for Ergonomic Product Classification Using Anthropometric Measurements
Measurement (2016)
  • Dr. Madjid Tavana, La Salle University
  • Mohammad Reza Kazemi, Mazandaran University of Science and Technology
  • Amin Vafadarnikjoo
  • Mohammadsadegh Mobin, Western New England University
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.
Keywords
  • ergonomic product classification,
  • anthropometric measurements,
  • artificial immune algorithm,
  • ergonomic product design,
  • meta-heuristic
Publication Date
Summer September 7, 2016
Citation Information
Madjid Tavana, Mohammad Reza Kazemi, Amin Vafadarnikjoo and Mohammadsadegh Mobin. "No TitleAn Artificial Immune Algorithm for Ergonomic Product Classification Using Anthropometric Measurements" Measurement Vol. 94 (2016) p. 621 - 629
Available at: http://works.bepress.com/MohammadRezaKazemi/1/