The development of clothing sizing system is the best way to provide the best suitable size in clothing design. A sizing system classifies a specific population into homogeneous subgroups based on some key body dimensions. The current project objective is to develop a clothing sizing system for Libyan adults based on anthropometric body measurements of Libyan adults between 18 and 25 years old. The aim of the current project is to examine anthropometric measurements for people, to collect body measurements of adults in Benghazi and analyze those using simple statistical methods to understand the body ranges and variations present for each gender and age group to develop sizing system of them. nineteen body dimensions were measured for each person to develop clothing sizing system. The measurements were gathered from a total of 60 adults (30 males and 30 females between 18 and 25 years old) from Benghazi. The anthropometric data were analyzed using Minitab program. ANOVA tests were used to identify differences between age groups, and t-test were used to identify differences between genders. The results of ANOVA showed that there are no differences between all the body measurements, and the results of t-test showed that there are differences between most of the body measurements. These differences were considered when developing sizing system. Pearson correlation coefficients analysis was carried out to determine the interrelationships between the various body measurements. From these findings it may be concluded that the weight is very strongly correlated with some other dimensions. The mean values and the standard deviation were used for creating size steps for the size chart. Three kinds of sizes were identified: L (large), M (medium) and S (small)..
@artical{s1322024ijsea13021005,
Title = "The Development of Sizing System for Clothes of Benghazian Adults Based on Anthropometric Data",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "13",
Issue ="2",
Pages ="17 - 21",
Year = "2024",
Authors ="Salima A. Bilhassan, Faeza S. Dlhin, Ragab M., Elaneizi, Fatma F., Bujawari, Noora O., Albarki"}