簡易檢索 / 詳目顯示

回結果列表
研究生： 蔡宏政
Tsai, Hung-Cheng
論文名稱： 電腦輔助產品造形、色彩設計與客製化商務系統建構之研究
The Construction of a Computer-aided Product Form Design, Color Planning, and Customization System
指導教授： 蕭世文
Hsiao, Shih-Wen
學位類別： 博士
Doctor
系所名稱： 規劃與設計學院 - 工業設計學系
Department of Industrial Design
論文出版年： 2004
畢業學年度： 92
語文別： 英文
論文頁數： 139
中文關鍵詞： 色彩計劃 、產品造形 、產品客製化 、產品設計
外文關鍵詞： color planning, product customization, product form, product design
相關次數： 點閱：122  下載：13 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 由於數值化加工製造技術的進步與成熟，在我們日常生活中的許多消費型產品，其機能層面已臻成熟發展階段。相對的，處於今日市場激烈競爭與產品生命週期極為短暫的環境之下，對於以開發新產品為重心的產業而言，有關產品的造形與色彩設計開發，益發顯得格外重要。但是，產品的造形與色彩關乎個人主觀的意象感覺認知，並不容易以一般的數量化方法進行研究分析。
    一般而言，工業設計師依據個人過去的刻板設計經驗進行黑箱式的產品概念設計作業。因此，為了輔助設計師能夠以較有效率且客觀的方式進行設計活動，本論文提出系統性的產品色彩計劃與造形設計方法，針對產品造形與色彩，建立一套關聯對應之意象評價模式。此外，亦針對消費者需求導向之基本理念，建立一套客製化產品量身定做服務的決策模式，輔助消費者選購合適的商品。
    在本論文所提出的研究方法中，分別應用模糊理論、灰色理論、倒傳遞類神經網路、遺傳基因演算法與層級分析法等方法論，針對消費者對於產品意象或需求等不確定性問題，建立系統之關聯、評價、搜尋與決策模式。並將建立之方法論導入適當的產品案例並予以程式化，據此發展成一套網路輔助產品色彩計劃、造形設計與客製化商務系統，以驗證其實務上之可行效能。藉由此輔助介面，設計師可經由設計參數的設定，迅速獲得有關產品造形與色彩設計的具體建議；並且消費者更可透過客製化的服務介面，將輸入的產品需求，量身轉換為最佳化的商品模組選購建議。

    Due to the remarkable advances achieved in numerically–controlled machining technology for product manufacture, the functional aspects of many of the consumptive products used in our daily lives are now fully matured. Subsequently, for enterprises seeking to develop new products in today’s highly competitive marketplace, which is characterized by short product life cycles, the apparent style of a product, i.e. its form and color, has assumed an ever-increasing importance. However, it is difficult to ascertain an individual’s psychological reaction to a particular product style from conventional numerical approaches.
    In general, industrial designers tend to utilize their own particular stereotyped design experiences when generating novel design concepts, and these experiences are still regarded as something of a black box. To assist designers in performing their design activities more efficiently and objectively, this dissertation presents several systematic methods for product-color planning and form design based upon database resources describing the relationships between product styles and their corresponding perceptual image evaluations. Additionally, a decision-making approach for consumer-orientated product customization services is proposed to assist consumers in purchasing their required products.
    By applying the theorems of fuzzy set theory, gray theory, back-propagation neural networks, genetic algorithms, and the analytic hierarchy process method on the proposed methods, it is possible to solve problems of uncertainty and to construct models of the product image relationship, and of the evaluation, searching, and decision-making algorithms associated with a consumer’s psychological feelings towards a particular product. An automatic web-aided product-color planning, form design, and product customization system is constructed on the basis of the developed methods and associated algorithms. Several consultative interfaces are established for the specified case studies to demonstrate the effectiveness of the developed system. Using these interfaces, the designer can obtain the embodied design suggestions of a particular product form and color by providing the required design parameters, and the consumer can acquire a customized product from the optimized combination of alternatives which match his or her inputted requirements.

    ABSTRACT I ACKNOWLEDGEMENTS III CONTENTS IV LIST OF TABLES IX LIST OF FIGURES XI NOMENCLATURE XIV 1 INTRODUCTION 1 1.1 CIE-BASED PRODUCT-COLOR PLANNING 2 1.2 FEATURE-BASED PRODUCT FORM DESIGN 4 1.3 CONSUMER-ORIENTED PRODUCT CUSTOMIZATION SERVICE 6 1.4 ORGANIZATION OF THE THESIS 8 2 THEORETICAL BACKGROUND 10 2.1 INTRODUTION 10 2.2 GRAY SYSTEM THEORY 10 2.2.1 Gray Relational Generating Operation 11 2.2.2 Gray Clustering Operation 12 2.3 FUZZY SET THEORY 13 2.3.1 Triangular Fuzzy Numbers and Linguistic Variables 13 2.3.2 Rule-based Fuzzy Conditional Statements 15 2.4 BACK-PROPAGATION NEURAL NETWORK 16 2.5 GENETIC ALGORITHMS 17 2.6 ANALYTIC HIERARCHY PROCESS 18 2.7 A COMPUTER-AIDED CONCEPTUAL DESIGN TOOL – VBOI 20 3 CIE-BASED PRODUCT-COLOR PLANNING USING GRAY SYSTEM THEORY 22 3.1 INTRODUTION 22 3.2 OUTLINE OF THE DESIGN MODEL 23 3.3 IMPLEMENTATION METHOD 25 3.3.1 Constructing Basic PC-based CRT Color Samples 25 3.3.2 Establishing the Relationships between Colors and Image Words 26 3.3.3 Forecasting Overall Color Image Evaluation by Means of Gray Clustering 27 3.3.4 Forecasting Overall Color Image Evaluation by Means of BPN 29 3.3.5 RMSE Comparisons of Evaluation Forecasting for Gray Theory and BPN 30 3.4 CASE STUDY 31 3.4.1 Constructing the Target 3-D Geometric Model 31 3.4.2 Questionnaire Design and Investigation 31 3.4.3 Analyzing the Colors of the Individual Components of a Baby Walker 34 3.4.4 Calculating the Image Evaluation for Unspecified Colors 34 3.4.5 Gray Clustering Prediction for the Overall Evaluation 36 3.4.6 BPN Prediction for the Overall Evaluation 38 3.4.7 Prediction Ability Comparison between the Gray Model and the BPN Model 39 3.4.8 Construction of an Internet-aided Color-planning Interface 41 3.5 CONCLUSION 42 4 FEATURE-BASED PRODUCT FORM DESIGN USING A HYBRID GENETIC FUZZY NEURAL NETWORK ALGORITHMS 44 4.1 INTRODUTION 44 4.2 FUZZY NEURAL NETWORK-BASED GENETIC SEARCHING 46 4.2.1 Linguistic Variables for Product Image Judgments 47 4.2.2 Fuzzy Neural Network-based Product Image Prediction 48 4.2.3 Product Form Search with Genetic Algorithms 50 4.3 IMPLEMENTATION PROCEDURES 51 4.3.1 Definition of the Feature-based Form Parameters 51 4.3.2 Selection of Image Words 55 4.3.3 Create Basic Test Samples 56 4.3.4 Generation of New Morphed Shapes 56 4.3.5 Implementation of Product Image Evaluation Measurement 58 4.3.6 Fuzzy Neural Network-based Prediction Model 59 4.3.6.1 Network Training 60 4.3.6.2 Recalling Stage 61 4.3.7 Genetic-based Product Form Search Model 62 4.3.8 Construction of the Operation System for Image Prediction and Form Search 63 4.4 CASE STUDY FOR PRODUCT FORM DESIGN 65 4.5 CONCLUSION 71 5 A LINGUISTIC EVALUATION MODEL FOR THE INTEGRATED SENSATION OF PRODUCT FORM AND COLOR 73 5.1 INTRODUTION 73 5.2 IMPLEMENTATION PROCEDURES 74 5.2.1 Definition of the Product Color and Form Parameters 74 5.2.2 Create Basic Test Samples 74 5.2.3 Questionnaire Design and Investigation for Linguistic Image Evaluation 75 5.2.3.1 Mono-color Image Test 76 5.2.3.2 Product-form Image Test 77 5.2.3.3 Integrated Product Image Test of the Specified forms and Colors 78 5.2.4 Fuzzy Neural Network-based Evaluation Model 79 5.2.4.1 Evaluation Model I 80 5.2.4.2 Evaluation Model II 81 5.2.4.3 Network Training 85 5.2.5 Comparisons of Image Prediction Abilities of Model I and Model II 85 5.2.6 Construction of an Automatic Design Interface for Rapid CAD Modeling and Image Evaluation 88 5.3 CASE STUDY 89 5.4 CONCLUSION 91 6 A PRODUCT CUSTOMIZATION MODEL USING FUZZY LOGIC 93 6.1 INTRODUTION 93 6.2 OUTLINE OF THE EVALUATION MODEL 94 6.3 CONSTRUCTION OF FUNDAMENTAL ALGORITHMS 96 6.3.1 Modified Utility Value on Triangular Fuzzy Numbers 96 6.3.2 Similarity Measure of Triangular Fuzzy Numbers Based on Modified Utility Values 100 6.3.3 Modified Geometrical Distance and Synthetic Distance Method 100 6.4 IMPLEMENTATION METHODS 102 6.4.1 Establishing Customer Needs 102 6.4.2 Establishment of Product Features and Associated Components 103 6.4.3 Construction of 3-D Configuration 104 6.4.4 Evaluation of Consumer Requirements 104 6.4.5 Establishing of Product Features and Their Relationship to Customer Needs 106 6.4.6 Fuzzy Inference Rule Setting for Feature Requirements 108 6.4.7 Calculation of Feature Requirements 110 6.4.8 Utility Similarity Measure for Feature Requirement 111 6.4.9 The Optimized Searching of Feasible Combinations 111 6.4.10 A Web-aided Stroller Customization Program 115 6.5 CASE STUDY FOR STROLLER CUSTOMIZATION 115 6.6 CONCLUSION 125 7 SUMMARY AND CONCLUSIONS 127 7.1 OVERVIEW OF CONCLUSIONS 127 7.2 SUGGESTIONS FOR FOLLOW-UP RESEARCH STUDIES 129 REFERENCES 130 PUBLICATION 138 VITA 139

    REFERENCES
    1. P.A. van Elsas, J.S.M. Vergeest. New functionality for computer-aided conceptual design: the displacement feature. Design Studies 1998; 19 (1): 81-102.
    2. F.E.H. Tay, J. Gu. Product modeling for conceptual design support. Computers in Industry 2002; 48: 143-155.
    3. M. Shpitalni, H. Lipson. 3D conceptual design of sheet metal products by sketching. Journal of Materials and Processing Technology 2000; 103: 128-134.
    4. S.W. Hsiao, H.C. Tsai. Fuzzy set theory on car-color design. Color Research and Application 1994; 19: 202-213.
    5. S.W. Hsiao. A systematic method for color planning in product design. Color Research and Application 1995; 20: 191-205.
    6. S. Ishihara, K. Ishihara, M. Nagamachi, Y. Matsubara. An automatic builder for a Kansei expert system using self-organizing neural networks. Int. J. of Industrial Ergonomics 1995; 15: 13-24.
    7. N. Cross. Engineering design methods. John Wiley & Sons, Chichester, 1994.
    8. J.C. Jones. Design methods. Van Nostrand Reinhold, New York, 1992.
    9. V. Hubka, W.E. Eder. Theory of technical systems. Spring-Verlag, New York, 1988.
    10. G.C. Van Dijk Casper. New insights in computer-aided conceptual design. Design Studies 1995; 16 (1): 62-80.
    11. J. Sun, D.K. Kalenchuk, D. Xue, P. Gu. Design candidate identification using neural network-based fuzzy reasoning. Robotics and Computer Integrated Manufacturing 2000; 16: 383-396.
    12. M. Tovey, J. Owen. Sketching and direct CAD modeling in automotive design. Design Studies 2000; 21 (6): 569-588.
    13. F.J. Vico, F.J. Veredas, J.M. Bravo, J. Almaraz. Automatic design synthesis with artificial intelligence techniques. Artificial Intelligence in Engineering 1999; 13 (3): 251-256.
    14. H.S. Kim, S.B. Cho. Application of interactive genetic algorithm to fashion design. Engineering Applications of Artificial Intelligence 2000; 13: 635-644.
    15. M. Nagamachi. Kansei engineering: a new ergonomic consumer-oriented technology for product development. International Journal of Industrial Ergonomics 1995; 15 (1): 3-11.
    16. T. Jindo, K. Hirasago, M. Nagamachi. Development of a design support system for office chairs using 3-D graphics. International Journal of Industrial Ergonomics 1995; 15 (1): 49-62.
    17. Y. Matsubara, M. Nagamachi. Hybrid Kansei engineering system and design support. International Journal of Industrial Ergonomics 1997; 19 (2): 81-92.
    18. S.M. Yang, M. Nagamachi, S.Y. Lee. Rule-based inference model for the Kansei engineering system. International Journal of Industrial Ergonomics 1999; 24: 459-471.
    19. S. Ishihara, K. Ishihara, M. Nagamachi, Y. Matsubara. An analysis of Kansi structure on shoes using self-organizing neural networks. International Journal of Industrial Ergonomics 1997; 19: 93-104.
    20. T. Tsuchiya, T. Maeda, Y. Matsubara, M. Nagamachi. A fuzzy rule induction method using genetic algorithm. Internal Journal of Industrial Ergonomics 1996; 18: 135-145.
    21. S.W. Hsiao, C.H. Chen. A semantic and shape grammar based approach for product design. Design Studies 1997; 18 (3): 275-296.
    22. S.W. Hsiao, M.S. Chang. A semantic recognition-based approach for car’s concept design. International Journal of Vehicle Design 1997; 18 (1): 53-82.
    23. S.W. Hsiao, M.C. Liu. A morphing method for shape generation and image prediction in product design. Design Studies 2002; 23 (5): 533-556.
    24. S.W. Hsiao, H.C. Huang. A neural network based approach for product form design. Design Studies 2002; 23 (1): 67-84.
    25. S.W. Hsiao, H.P. Wang. Applying the semantic transformation method to product form design. Design Studies 1998; 19 (3): 309-330.
    26. M.S. Sanders, E.J. McCormick, Human factors in engineering and design. McGraw-Hill, New York, 1993.
    27. L.A. Zadeh. Fuzzy set. Information and Control 1965; 8: 338-353.
    28. R.E. Bellman, L.A. Zadeh. Decision-making in a fuzzy environment. Management Sci. 1970; 17 (4): 141-164.
    29. C.T. Chen. A fuzzy approach to select the location of the distribution center. Fuzzy Sets and Systems 2001; 118: 65-73.
    30. C.H. Hsieh, S.H. Chen. A model and algorithm of fuzzy product positioning. Information Sciences 1999; 121: 61-82.
    31. T.L. Saaty. The analytic hierarchy process. McGraw-Hill, New York, 1980.
    32. M. Weck, F. Klocke, H. Schell, E. Ruenauver. Evaluating alternative production cycles using the extended fuzzy AHP method. European Journal of Operational Research 1997; 100: 351-366.
    33. J.L. Deng. Essential topics on grey system: theory and applications. Huazhong University of Science and Technology Press, Wuhan, 1987.
    34. J.L. Deng. Introduction to grey system theory. Journal of Grey System 1989; 1: 1-24.
    35. Z. Peng, T.B. Kirk. Wear particle classification in a fuzzy grey system. Wear 1999; 225-229: 1238-1247.
    36. S.H. Chang, J.R. Hwang, J.L. Doong. Optimization of the injection molding process of short glass fiber reinforced polycarbonate composites using grey relational analysis. Journal of Materials Processing Technology 2000; 97: 186-193.
    37. C.L. Chang, C.C. Wei, C.B. Chen. Concurrent maximization of process tolerances using grey theory. Robotics and Computer Integrated Manufacturing 2000; 16: 103-107.
    38. Y.P. Huang, C.C. Huang. The integration and application of fuzzy and grey modeling methods. Fuzzy Sets and Systems 1996; 78: 107-119.
    39. C.I. Hsu, Y.H. Wen. Application of grey theory and multiobjective programming towards airline network design. European Journal of Operational Research 2000; 127: 44-68.
    40. G. Sun. Prediction of vegetable yields by grey model GM(1,1). Journal of Grey System 1991; 2: 187-197.
    41. S.H. Chen. Operations on fuzzy numbers with function principle. Tamkang Journal of Management Sciences 1985; 6 (1): 13-25.
    42. C.H. Hsu, B.C. Jiang, E.S. Lee. Fuzzy neural network modeling for product development. Mathematical and Computer Modelling 1999; 29: 71-81.
    43. A. Kaufmann, M.M. Gupta. Introduction to fuzzy arithmetic: theory and applications. Van Nostrand Reinhold, New York, 1985.
    44. L.A. Zadeh. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transaction on Systems, Man, and Cybernetics 1973; SMC-3 (1): 28-44.
    45. S.V. Wong, A.M.S. Hamouda. Development of genetic algorithm-based fuzzy rules design for metal cutting data selection. Robotics and Computer Integrated Manufacturing 2002; 18: 1-12.
    46. S. Heilpern. Representation and application of fuzzy numbers. Fuzzy Sets and Systems 1997; 91 (2): 259-268.
    47. J.A. Freeman, D.M. Skapura. Neural networks algorithm, application, and programming techniques. Addison-Wesley, New York, 1991.
    48. J. Hertz, A. Krough, R.G. Palmer. Introduction to the theory of neural computation. Addison-Wesley, New York, 1991.
    49. D.E. Goldberg. Genetic algorithms in searching, optimization and machine learning. Addison-Wesley, Reading, Massachusetts, 1989.
    50. M. Gen, R. Cheng. Genetic algorithms and engineering design. John Wiley & Sons, New York, 1997.
    51. Y.P. Huang, C.H. Huang. Real-valued genetic algorithms for fuzzy grey prediction system. Fuzzy Sets and Systems 1997; 87 (3): 265-276.
    52. S.V. Wong, A.M.S. Hamouda. Optimization of fuzzy rules design using genetic algorithms. Advances in Engineering Software 2000; 31: 251-262.
    53. F. Erbatur, O. Hasancebi, I. Tutuncu, H. Kilic. Optimal design of planar and space structures with genetic algorithms. Computers & Structures 2000; 75: 209-224.
    54. N. Marco, S. Lanteri. A two-level parallelization strategy for genetic algorithms applied to optimum shape design. Parallel Computing 2000; 26: 377-397.
    55. F. Herrera, E. Lopez, C. Mendana, M.A. Rodriguez. A linguistic decision model for personnel management solved with a linguistic biobjective genetic algorithms. Fuzzy Sets and Systems 2001; 118: 47-64.
    56. X.T. Zhang, H.Y. Zhu, H.B. Zhang. Robust grey model based on genetic algorithms and its application to prediction for chromatographic retention. Chemometrics and intelligent Laboratory Systems 1998; 44: 197-203.
    57. EDS Corporation. Open I-DEAS programming course guide. 2001.
    58. C. Rainwater. Light and color. Western Publishing Company, New York, 1971, 130 p.
    59. D.L. MacAdam. Color theory and its application in art and design. Springer-verlag, Berlin, 1987, p 48-49.
    60. S.H. Chen. Ranking fuzzy numbers with maximizing set. Fuzzy Sets and Systems. 1985; 17: 113-129.
    61. K.C. Hui, Y. Li. A feature-based shape blending technique for industrial design. Computer-Aided-Design 1998; 30 (10): 823-834.
    62. M. Belaziz, A. Bouras, J.M. Brun. Morphological analysis for product design. Computer-Aided-Design 2000; 32 (5-6): 377-388.
    63. Beier. Feature-based image metamorphosis. ACM Computer Graphics 1992; 26 (2): 35-42.
    64. G. Brunetti, B. Golob. A feature-based approach towards an integrated product model including conceptual design information. Computer-Aided Design 2000; 32: 877-887.
    65. S.W. Hsiao, J.C. Chuang. A reverse engineering based approach for product form design, Design Studies 2003; 24 (2): 155-171.
    66. S.E. Chen, R.E. Parent. Shape averaging and its applications to industrial design. IEEE Computer Graphics and Applications 1989; 9 (1): 47-54.
    67. T.W. Sederberg, E. Greenwood. A physically based approach to 2-D shape blending. ACM Computer Graphics 1992; 26 (2): 25-34.
    68. M. Shapira, A. Rappport. Shape blending using the car-skeleton representation. IEEE Computer Graphics and Applications 1995; 15 (2): 44-50.
    69. H. Wang. An approach to computer-aided styling. Design Studies; 1995; 16 (1): 50-61.
    70. Y. Ujiie, Y. Matsuoka. Shape-generation method using curvature entropy. ASME International Mechanical Engineering Congress and Exposition, Recent Advances in Design for Manufacture (DFM); 2000; 85-92.
    71. R.J. Kuo, C.H. Chen, Y.C. Hwang. An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network. Fuzzy Sets and Systems 2001; 118: 21-45.
    72. A. Akgunduz, D. Zetu, P. Banerjee, D. Liang. Evaluation of sub-component alternatives in product design processes. Robotics and Computer Integrated Manufacturing 2002; 18: 69-81.
    73. D. Dubois, H. Prade. Operations on fuzzy numbers. International Journal of Systems Science; 1978: 9 (6): 613-626.

    下載圖示 校內：立即公開
    校外：2004-02-04公開
    QR CODE