Developing Female Size Charts for Facilitating Garment Production by Using Data Mining

應用資料挖礦技術發展女性成衣生產尺碼圖

10.29977/JCIIE.200705.0007

徐志宏(Chih-Hung Hsu)；林海芬(Hai-Fen Lin)；王茂駿(Mao-Jiun Wang)

人體計測資料 ； 資料挖礦 ； 尺碼圖 ； 成衣生產 ； anthropometric data ； data mining ； size charts ； garment production

工業工程學刊

24卷3期（2007 / 05 / 01）

245 - 251

英文

資料挖礦已經成功地應用在許多領域，但在建立女性成衣設計與生產的尺碼圖上，卻未見相關的研究。本研究目的是以聚類分析為基礎的資料挖礦技術挖掘台灣女性人體計測資料來發展成衣尺碼圖。研究結果顯示，使用資料挖礦循環所建立的尺碼圖有較高的尺碼覆蓋率、較少的尺碼組數，而且根據尺碼圖的分配比例與體型也可以提供生產者作為成衣生產的參考。此外，由於人體計測資料庫必須不斷地更新，尺碼圖可經由本研究所建議的資料挖礦循環持續更新，除使設計更符合消費者需求外，對生產規劃與降低存貨成本也將有所助益。

Data mining has been successfully applied in many fields. However, little research has been done in the area of developing female size charts for consumer garment design. Focusing on the anthropometric data of adult females in Taiwan, the goal of this study was to develop garment-size charts, using a cluster-based data mining approach. Certain advantages may be observed when 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 an anthropometric database must be repeatedly updated, size charts may also be continuously renewed via application of the proposed data mining cycle. These newly developed size charts will remain continually beneficial for both production planning and reducing inventory costs, while facilitating the production of garments.

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