This paper aimed to use data mining techniques in establishing standard sizing system for Sudanese army officers garment based on an anthropometric body measurements variables. The anthropometric data was collected from Sur military clothing factory in Sudan. The data set collected for 841 army officers was used. For each individual 13 anthropometric variables were involved. In this research data mining methods (WEKA and SPSS) were used for clustering and establishing sizing system. The K-means algorithm was implemented to determine the final cluster classification in two stages in the first stage, the (WEKA) clustering method was applied on the original database to categories the size figures. The (SPSS) method, as quantitative approach, was used in the second stage in order to generate descriptive statistics for the raw data following a step by step procedure. Cluster analysis using chest and waist as a control anthropometric variables revealed eight distinct clusters namely; XS, S, M, L, XL, XXL, XXXL and XXXXL respectively. Size codes and upper and lower size limits are generated.
Data mining, anthropometric variables, garments industry, sizing chart, clustering
