Title
An artificial immune algorithm for ergonomic product classification using anthropometric measurements
Document Type
Article
Publication Date
9-7-2016
DOI
https://doi.org/10.1016/j.measurement.2016.09.007
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.
Language
English
Recommended Citation
Tavana, Madjid; Kazemi, Mohammad Reza; Vafadarnikjoo, Amin; and Mobin, Mohammadsadegh, "An artificial immune algorithm for ergonomic product classification using anthropometric measurements" (2016). Business Systems and Analytics Faculty Work. 150.
https://digitalcommons.lasalle.edu/bsa_faculty/150
Comments
Tavana, M., Kazemi, M.R., Vafadarnikjoo, A. and Mobin, M. (2016) ‘An Artificial Immune Algorithm for Ergonomic Product Classification Using Anthropometric Measurements,’ Measurement, Vol. 94, pp. 621-629.