鞋楦是鞋子製作的首要工作，它不僅呈現出鞋子的外形與流行美感，而更重要的是直接影響人體足部穿上鞋子時舒適與否，因此鞋楦必需根據人體計測，以其足部的形狀以及機能加以設計製作；而也由於每個人的腳型不盡相同，在大量製造要求的標準規格下，所設計出來的鞋楦，並不能完全符合每一個人獨特的足型。本研究的目的在於利用逆向工程掃描技術，取得個人足部以及鞋楦外觀資料，也針對鞋楦設計所需之主要幾項足型特徵，藉由切層演算法(Slicing Algorithm)發展系統程式，以自動擷取足型特徵資料；並以人體工學理論，在鞋楦與個人的腳型上，建立一模糊的設計關連，並導入模糊理論(Fuzzy Theory)，以分析足部以及鞋楦的特徵資料；此外，再藉由層級分析法(Analytic Hierarchy Process)分析特徵資料，得到其重要性的相對權重；最後完成搜尋、排序，得到最接近、適合個人足型之鞋楦。而此鞋楦可根據本研究所得之各項特徵與圖形資料，可再加以修改，達到客製化鞋楦的目的。 The shoe lasts are the first work to produce shoes. They not only show the shape and the fashion of the shoes, but also directly affect the comfort as people wear the shoes. The shoe last must be designed and manufactured by the anthropometry which is concerned with the shape and the function of the human feet. Because of the difference of each one’s unique feet, the shoe lasts which are designed within the standard specifications would not completely fit them. For the purpose of the research, reverse engineering scanning technology is used to obtain the outline data of the shoe lasts and the human feet, and a programmed system of slicing algorithm would be developed to automatically capture the feature data which is needed for the shoe last design. Besides, there is a fuzzy design relationship of ergonomics between the shoe lasts and the human feet, so the fuzzy theory can be used to analyze these feature data of the last and the human feet. Finally, the weights of these features for ergonomics would be found by Analytic Hierarchy Process (AHP). Through the searching and ranking with the data mentioned above, a optimal shoe last will be found.
