Using Data Mining Framework to Eztract Sizing Knowledge for Facilitating Advanced Apparel Manufacture
Apparel production is a high value-added industry in the global textile manufacturing chain. Standard size charts of apparel ergonomics are crucial issue, play an even important role for apparel manufacturing industry. The extraction of knowledge from large database has been successfully applied in a number of advanced fields by data mining. However, little research has been done in the area of developing standard size charts of apparel manufacture, using anthropometric data. Focusing on the anthropometric data of adult females in Taiwan, the goal of this study was to develop standard size charts, using a novel cluster-based data mining framework. Certain advantages may be observed when standard size charts are developed, using the data mining cycle. These include being able to cover a higher percentage of the population, using fewer sizes, and providing manufacturers with reference points to promote products, according to body type and distribution. Since the anthropometric database must be repeatedly updated, standard size charts may also be continuously renewed via application of the proposed data mining framework. These standard size charts will remain continually beneficial for both production planning and reducing inventory costs, while facilitating the advanced manufacture for apparel manufacturing industry.
Data mining Anthropometric data Apparel manufacture Standard size charts
Chih-Hung Hsu Hui-Ming Kuo Bor-Shong Liu
Department of Industrial Engineering and ManagementHsiuping Institute of Technology Taichung 41249, Department of Logistics Management,Shu-Te University No.59, Hun Shan RD., Yen Chau, Kaohsiung, Taiwa Department of Industrial Engineering and Management, St. Johns University 499, Sec. 4, Tam King RD.
国际会议
17th World Congress on Ergonomics(第十七届国际人类工效学大会)
北京
英文
1-4
2009-08-09（万方平台首次上网日期，不代表论文的发表时间）