Mining the body features to develop sizing systems to improve business logistics and marketing using fuzzy clustering data mining

Authors:
Chih-Hung Hsu;Tzu-Yuan Lee;Hui-Ming Kuo
Affiliations:
Department of Industrial Engineering and Management, Hsiuping Institute of Technology, Taichung County, Taiwan, R.O.C.;Department of Industrial Engineering and Management, Hsiuping Institute of Technology, Taichung County, Taiwan, R.O.C.;Department of Logistics Management, Shu-Te University, Kaohsiung County, Taiwan, R.O.C.
Venue:
WSEAS Transactions on Computers
Year:
2009

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Abstract

Business logistics have played an important role of business operations of procurement, purchasing, inventory, warehousing, distribution, transportation, customer support, financial and human resources. Human body type classifications are also very crucial issue for garment manufacturing. Data mining has been widely used in many fields. But, there is lack of research in the area of establishing of garment-sizing systems for business logistics. This research aims to establish sizing systems of body types from the anthropometric data of females by using a fuzzy clustering-based data mining approach. Certain advantages may be observed when the sizing systems are established, using fuzzy clustering-based data mining procedure. Body types could be accurately classified for garment production according the newly the sizing systems. This approach is found to be effective in processing the anthropometric data, and obtaining regular rules for the development of sizing systems. The results of this study can provide an effective procedure of identifying the clusters of human body type to establish the sizing systems for integrating logistics operations internally with different functions inside the organization and also externally with business partners.