隨著電子科技的發展與普及，導致3C（Compute - Communication - Consumer Electronic）產品的汰換率不斷升高，以及生命週期的大幅縮短，而消費者對3C產品的持有率與需求不斷提昇，各企業都需求推出更多元化的創新產品。而顧客族群的多元化使設計師難以掌握顧客對產品的喜好，且過往最適化造形研究多採用以部件或規格分類，產生之最佳解未必如實符合顧客需求，加上設計系統的發展多包含各種數學演算機制，而缺乏整合性之操作介面，將難以應用於各種背景之使用者。
綜合上述背景，本研究選定「觸控式屏幕PDA（Personal Digital Assistant）手機」作為目標產品，經由集群分析市面產品，建立觸控式屏幕PDA手機各類型分群與代表性樣本，並應用灰關聯分析來獲取與產品外形喜好差異關聯度較高的個人特質項目清單，再以形態分析對各分群進行外形構成要素解析，依據數值的分布建立產品參數化規則與限制，以此參數化規則建構產品的原形3D模型，最後應用倒傳遞類神經網路與物件導向的概念，建構本研究欲發展之產品外形設計系統，並對完成之系統進行類神經誤差驗證與推薦外形的評價驗證，讓本研究發展之產品外形設計系統在應用上，可同時達到快速設計與貼近顧客需求兩個重要的指標，並將顧客需求反映到產品設計的過程中。
本研究整合多元的技術與系統軟體，提出透過灰關聯與類神經網路理論，能確實獲取顧客個人特質與對產品喜好之間的關係性，並以此關係性為依據建構產品外形設計系統，經由系統實例演練的驗證過程，說明產品設計系統能確實衍生貼近顧客喜好之產品外型，而在系統發展上以人性化之系統介面設計，使系統可貼近不同領域背景之使用者，在未來應用性上可大幅提升其效用。

With the development and popularization of electronic technology, cause the replacement rate of 3C products continue to rise, and shortened the product's life cycles. This phenomenon also rise the holding rate and customers’ requirement of 3C products, cause the companies demand to have more diversified product innovation. And the diverse customer groups make designers difficulty figured out the customer references of products, and the past reserch about optimal form of products, mostly classify with components or specifications, and the optimal solution may not accurately meet customer needs, and with the development of the design system contains a variety of multi- mathematical calculation mechanism, and the lack of integration of the user interface, will be difficult to apply to the users with varied backgrounds.
Above the background, in this study, we selected “touch-screen PDA mobile phone” as the target product, and using cluster analysis to define the types of target product and typical sample product in which type, and then applied gray-relation analysis to obtain the customer personal characteristics list which have higher connection with preferences of product form, and then using morphological analysis to establish the rules and limits of products’ parametric, and created the product original 3D model according to these rules and limits, and applied the back-propagation neural network and object-oriented concepts to build the product form design system of this study, and then verified the neural network error and evaluation of the product form design system, make this system can achieve two important indicators about rapid design and close to customers’ requirements, and reflected the customer needs in the process of product design.
In this study, we integrate the multiple technology and system software, and interpreted that apply the theory of gray relation and neural network can actually obtains the relationship between the customers’ personal characteristics and preferences of the product, and use this relationship as the basis to create the product form design system, Instance of the specific case experiment and the system validation process, showing that the product design system can recommend the product form which indeed close to the customer, and with the development of the humanity system interface design, the system can be metch to the different background of users, and enhancein the system effectiveness of the application in the future.

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