Volume 4, Issue 1, June 2019, Page: 24-31
Application of Fuzzy Clustering Methodology for Garment Sizing
Adepeju Abimbola Opaleye, Department of Industrial and Production Engineering, University of Ibadan, Ibadan, Nigeria
Adekunle Kolawole, Department of Industrial and Production Engineering, University of Ibadan, Ibadan, Nigeria
Oliver Ekepre Charles-Owaba, Department of Industrial and Production Engineering, University of Ibadan, Ibadan, Nigeria
Received: Apr. 16, 2019;       Accepted: May 28, 2019;       Published: Jun. 12, 2019
DOI: 10.11648/j.ajdmkd.20190401.15      View  569      Downloads  89
With the growing demand for Ready-To-Wear outfits especially in African textile prints, the currently used European, American and Asian garment sizing systems seems unsuitable for the Nigerian garment industry where customer’s choose clothing item not only due to fit in terms of body measurements but also the dress culture, style, preference and some other implicit requirements. This study aims to develop a size chart for different styles of trousers worn by Nigeria male population. Anthropometric data of 500 customers were taken in a natural random process and from stable tailoring establishments. The data was analysed using descriptive statistics and the fuzzy clustering methodology (FCM) was used as a suggestive approach which describes subjectivity in customer preferences. Analysis of the FCM output shows that the number of individual measurements with misfit has no significant difference (Festimated= 1.119, p-value=0.375 and Fcritical= 2.866) across cluster. The percentages of misfit were 38.0, 23.4, 31.6, 31.4 and 3.8% for hip measurement, length, waist, thigh and bottom-girth respectively. The developed sizing system which reflects subjectivity in customer’s selection of trouser may also enhance both producer and retailer’s production and replenishment policy.
Ready-To-Wear, Size Chart, Trousers, Fuzzy Clustering
To cite this article
Adepeju Abimbola Opaleye, Adekunle Kolawole, Oliver Ekepre Charles-Owaba, Application of Fuzzy Clustering Methodology for Garment Sizing, American Journal of Data Mining and Knowledge Discovery. Vol. 4, No. 1, 2019, pp. 24-31. doi: 10.11648/j.ajdmkd.20190401.15
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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