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研究生:陳勝懋
研究生(外文):Chen, Sheng-Mao
論文名稱:整合感性工學與人工智慧技術應用於產品造型設計之研究
論文名稱(外文):Study on the Application of Integral Schemes of Kansei Engineering and Artificial Intelligence on Product Form Design
指導教授:王焜潔王焜潔引用關係
指導教授(外文):Wang, Kun-Chieh
學位類別:碩士
校院名稱:嶺東科技大學
系所名稱:資訊科技應用研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
中文關鍵詞:感性工學徑向基類神經網路產品設計人工智慧適應性類神經網路模糊推論系統灰系統理論專家系統
外文關鍵詞:Kansei engineeringradial basis neural networkproduct designArtificial intelligenceANFISGrey system theoryExpert system
相關次數:
  • 被引用被引用:7
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在國際化趨勢,企業為了生存與發展必須不斷地推出新產品。而新產品的開發雖為企業帶來利潤與效益,卻也相對存在著風險。探討產品失敗的原因,有些是未能正確掌握消費者需求;有些則是設計師與客戶溝通不良使得開發時間過長,喪失了新產品上市的時機。
因此,為了正確掌握消費者的需求,本研究應用了感性工學技術來掌握消費者對於產品外型的感覺,並利用人工智慧技術來預測消費者對於產品的感覺,進一步製作一套產品設計專家系統。
本研究選定「手錶」與「MP3播放器」為實驗產品,經由MDS分析及K-means分群法來挑選市面上最具代表性的商品後,利用造型解構,找出產品組成的基本元素,然後利用最具代表性的產品分析所得的造型法則及基本元素。定義出每個構件特徵參數合理變化樣式,再透過型態學圖表,排列組合已衍生出多種造型,再以人工智慧技術建立出造型特徵參數與感性語彙之關係模式。
將資料處理過後的結果建立語彙造型資料庫,建構出一個專家系統,輔助設計者能輕易的建立一個符合消費者需求的產品,經由此系統設計出來之產品可正確符合消費者心中意象,充分發揮產品設計效能,並縮短產品開發時間,以提高產品競爭力。
To meet the trend of globalization, enterprise must continually develop new products to survive. Although new products have been bring profit and benefit, but they are not risk free. The reasons that cause failure of newly developed products partly come from wrong information of customer’s needs and partly come from inadequate communications between designers and customers. These failure effects certainly would induce losses of opportunity for marketing.
Therefore, in order to correctly catch the customer’s demands, here we use the technique of Kansei engineering in conjunction with the artificial intelligence to establish a product design expert system.
In this study, we choose “watch” and “mp3 player” as the target products for demonstration. Through the operations of MDS, K-means method, morphological decomposition, and artificial intelligence technique, a precise relationship between Kansei words and characteristics of product shape can be established.
Furthermore, a design expert system is built via these schemes. With the help of this design expert system, designers can easily construct the product which meets the customer’s needs, attains good performance and shortens the development time, so as to promote the competitive ability of designed products.
目錄 1
圖目錄 4
表目錄 6
第一章 緒論 7
第一節 前言 7
第二節 研究動機 7
第三節 研究目的 7
第四節 研究範圍與限制 8
第五節 研究方法與架構 8
第二章 相關文獻探討 11
第一節 感性工學 11
壹、感性工學的定義與範圍 11
貳、感性工學之定義 13
第二節 類神經網路 15
第三節 統計分析技術 16
壹、集群分析 16
貳、多元尺度法(MDS) 17
叁、因素分析法 18
肆、假設檢定 19
第四節 專家系統 19
壹、CATIA程式之VB Editor開發工具 19
第五節 型態分析法 20
第六節 分析層級程序法(AHP) 21
第三章 研究理論架構 23
第一節 感性工學 23
壹、感性工學之程序 23
貳、感性工學施行手法 25
第二節 人工智慧技術 27
壹、徑向基類神經網路(RBFNN) 27
貳、適應性網路模糊推論系統 29
叁、倒傳遞類神經網路 36
肆、灰系統理論 40
第三節 統計分析技術 42
壹、因素分析法(Factor Analysis) 42
貳、集群分析(Cluster Analysis) 44
叁、多元尺度評量(Multidimensional Scaling Analysis) 49
肆、多配對樣本的Kendall協同係數檢定 50
第四節 語意差異法 50
第五節 問卷調查之樣本數 51
第四章 專家系統建置與流程 52
第一節 軟體需求 52
第二節 硬體需求 53
第三節 介面設計與流程 53
第五章 產品造型設計-手錶 54
第一節 找出代表性商品 54
壹、樣本蒐集 54
貳、群化分析 54
叁、集群分析-代表性商品選定 54
第二節 形容詞篩選 60
壹、蒐集形容詞語彙 60
貳、形容詞初步篩選 60
叁、形容詞二次篩選 61
第三節 造型之型態分析與解構 62
第四節 實驗樣本之選定 63
第五節 應用感性工學建立產品樣本感性評量矩陣 64
第六節 特徵參數與感性語彙間關係之建立 65
壹、徑向基類神經網路分析-正向分析 65
貳、徑向基類神經網路分析-反向分析 68
第七節 手錶造型設計專家系統之建置 70
壹、程式操作流程圖 70
貳、介面操作說明 71
第六章 產品造型設計-MP3播放器 76
第一節 找出代表性商品 76
壹、樣本蒐集 76
貳、群化分析 76
叁、集群分析-代表性商品選定 76
第二節 形容詞篩選 83
壹、蒐集形容詞語彙 83
貳、形容詞初步篩選 84
叁、形容詞二次篩選 84
肆、AHP分析 85
伍、AHP一致性檢定 86
第三節 造型之型態分析與解構 86
第四節 實驗樣本之選定 93
第五節 應用感性工學建立產品樣本感性評量矩陣 94
壹、多配對樣本的Kendall協同係數檢定 94
貳、建立感性評量矩陣 94
第六節 特徵參數與感性語彙間關係之建立 95
壹、倒傳遞類神經網路分析-正向分析 95
貳、ANFIS分析與灰色理論權重分析-反向分析 96
第七節 MP3播放器造型設計專家系統 104
壹、程式操作流程圖 104
貳、介面操作說明 107
第七章 結論與未來展望 117
第一節 結論 117
第二節 未來展望 118
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