設計師在產品的開發過程中，對於功能執行的品質改善，往往受制於主觀的產品評價，以致於無法確保產品的設計品質為最理想狀況。隨著製造技術的改進與電腦輔助設計工具的廣泛應用，產品設計得以有更多元的解決設計問題方法。因此，若能在執行產品設計之前，先尋求產品最理想的品質輸出效能，則此一產品設計方案，將更能符合產品設計的要件。
本研究基於品質工程中，以直交表配置之實驗數據轉換為訊號雜音比，來尋求最適組合之設計參數與水準的技法上，仍有藉助主觀決策的缺撼，特提出結合類神經網路與基因演算法則，於最適產品特徵之參數水準值的求取。最後，則將所求得之參數水準值，導入實際產品特徵之建構。本研究之發展並以電風扇之品質設計為案例，建構一結合類神經網路與基因演算法則之最適化搜尋平台。其所獲得之參數水準值，則運用離散繪圖原理於扇網與扇葉之造形設計。
本研究之結果，將可協助設計師整合品質工程與類神經原理於產品之開發與設計。

Due to the subjective evaluation in the product development process, designers have difficulty in ensuring that the improvement of product functional performance is in an optimum condition. However, the progress in manufacturing technology and the application of computer-aided design tools have made designers use more efficient ways to solve design programs. Therefore, designers look for product optimum quality outputs before product design will promise the design can meet the specified user requirements.
The objective of this research is to integrate neural network and genetic algorithm into quality engineering to improve the subjective selection of factor levels when dealing with the orthogonal arrays of design experiments. The design of an electric fan is chosen as a case. During the development process, an optimum search framework that integrates the neural network and genetic algorithm is constructed to help search for an optimum combination of factor levels from the experiment data. Finally, the concepts of fractal and computer graphics are applied in the nets and leaves of form design of an electric fan based on the optimum combination of factor levels.
It is expected that the results will provide designers with a useful way in integrating quality engineering and neural network into the product development and design.

一、中文部份
周宏坤，應用品質工程於產品設計資訊之決策分析，國立成功大學工業設計學系碩士論文， 民國82年。
周政宏，神經網路-理論與實務，松崗電腦圖書資料公司，台北，民國84年。
林昱甫，基因演算法在控制系統設計之應用，國立成功大學航空太空工程學系碩士論文，民國88年。
林志遠，軸流風扇的性能提昇設計與測試，國立成功大學航空太空工程學系碩士論文，民國86年。
吳乙鴻，應用類神經遺傳演算法建立電腦輔助設計模式之研究，國立成功大學工業設計學系碩士論文，民國82年。
胡佑宗 編譯，Benhard E. Bürdek 著，「工業設計-產品造型的歷史、理論及實務」，亞太圖書出版社，台北市，民國86年。
陳文印，設計解讀-工業設計專業知能之探索，亞太圖書出版社，台北市，民國86年。
張志三，漫談碎形 = A Talk About Fractals，牛頓出版社，民國85年。
張華城，應用類神經網路模式於產品造形特徵辨識之研究，國立成功大學工業設計學系碩士論文，民國88年。
張淑譽 編譯，James Gleick 著，混沌 :/開創新科學，上海譯文出版發行，上海，民國89年。
曾文曲 編譯，Falconer, K. 著，分形幾何：數學基礎及其應用，東北大學出版社，民國80年。
蔡明之 編譯，鷲尾泰俊 著，盧淵源 校訂，「實驗計劃法」，華泰圖書文物公司，台北市，民國80年。
黎正中 編譯，穩健設計之品質工程，台北圖書有限公司，台北市，民國82年。
葉怡成，網神經網路-模式應用與實作，第五版，儒林圖書出版社，台北市，民國87年。
謝錦志，赫斯特現象與碎形理論之研究，國立成功大學水利及海洋工程研究所碩士論文，民國85年。
羅華強，類神經網路-MATLAB的應用，清尉科技出版社，台北市，民國90年。
蘇朝墩，產品穩健設計-田口品質工程方法的介紹和應用，中華民國品質學會，台北市，民國86年。
蘇木春與張孝德，機器學習-類神經網路、模糊系統以及基因演算法則，全華科技圖書股份有限公司，台北市，民國91年。
二、英文部份
Addelman, S., “Orthogonal main effect plans for asymmetrical factorial experiments,” Journal of Technometrics, Vol.4, pp.21-46, 1962.
Arai, M.A., “Schemas and Neural Networks for Sixth Geberation Computing,” Journal of Parallel and Distributed Computing, Vol.6, No.2, pp.185-216, 1989.
Aubert, H. and Jaggard, D.L., “Wavelet analysis of transients in fractal superlattices,” Journal of Antennas and Propagation, Vol.50, No.3, pp.338-345, 2002.
Baliarda, C.P., Romeu, J. and Cardama, A., “The Koch monopole: a small fractal antenna,” Journal of Antennas and Propagation, Vol.48, No.11, pp.1773-1781, 2000.
Belew, R.K. and Booker, L.B., Proceedings of the Four International Conference on Genetic Algorithms, Morgan Kaufmann, 1991.
Belew, R.K, “Artificial life：a constructive lower bound for artificial intelligence,” Journal of Expert, Vol.6, Issue: 1, pp.8-15, 1991.
Chiang, P. and Chen, M.R., “Device optimization using response surface methodology with orthogonal arrays,” Proceedings, The 6th IEEE Inter workshop on Statistical Methodology, pp.17-20, 2001.
Che, H., Zheng, S. and Hong, X., “Integrated model for performance analysis of multiple class-of-service internet,” Communications, IEEE Proceedings, Vol.149, Issue: 3, pp.139-146, 2002.
Cochran, W.G. and Cox, G.M., Experiment design, John Wiley and Sons, 1957.
Cohen, L., “Quality function development and application perspective from digital equipment corporation,” Journal of National Productivity Review, Vol.7, No.3, pp.197-208, 1988.
Cybenko, G., “ Machine learning,” Computing in Science & Engineering, Vol.3, Issue: 3, pp.95-96, 2001.
Cheng, R. and Gen, M. , “Loop layout design problem in flexible manufacturing system using genetic algorithms,” Computers and Engineering , Vol.34, No.1 , pp.53-61, 1998.
David, G., “Robust decision-making for engineering design,” Journal of Engineering Design, Vol.12, No.1, pp.3-13 , 2001.
Dasgupta, D. and McGregor, D.R., “Genetically designing neuro-controllers for a dynamic system,” Neural Networks, Vol.3, pp.2951-2954, 1993.
Firmo, H.T. and Legey, L.F.L, “Generation expansion planning:An iterative genetic algorithm approach,” IEEE Transaction on Power Systems, Vol.17, No.3, 2002.
Goldberg, D.E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
Hagan, M.T., Demuth, H.B. and Beale, M., Neural Network Design, PWS Publishing Company, Boston, 1996.
Hearn, D. and Baker, M.P., Computer Graphics, Prentice Hall, Inc., Englewood Cliffs, New Jersey, 1986.
Heydt, G.T., “Power quality engineering,” IEEE Power Engineering Review , Vol.21, Issue:9, pp.5-7, 2001.
Hirasawa, K., Hu J., Murata, J., Jin C., Etoh, H. and Katagiri, H., “Universal learning networks with varying parameters,” Journal of Neural Networks, vol.2, pp. 1302-1307, 1999.
Holland, J. H., Adaptation in Natural and Artificial System, University of Michigan Press, 1992.
Huffman, H.J., “Energizing software engineering education through real-world projects as experimental studies,” Proceedings, The 15th Conference on Software Engineering Education and Training, pp.192-206, 2002.
Ichimura T., Oeda S. and Yoshida K., “An adaptive evolutional neuro learning method using genetic search and extraction of rules from trained networks,” Journal of Evolutionary Computation, Vol.2, pp.1343-1350, 2001.
Kigami, J., Analysis on Fractals, Cambridge University Press, 2001.
Kumar, K.K. and Smuda, E. ,“Robust controll using ga-optimized neural networks,” Journal of Control Applications, Vol.3, pp.1573-1578, 1994.
Kusiak, A., Computational Intelligence in Design and Manufacturing, John Wiley & Sons, Inc., New York, 2000.
Lavian, T. and Wang, P.Y., “Active networking on a programmable networking platform,” Proceedings, Open Architectures and Network Programming, pp.95-103, 2001.
Michalewicz, Z., Gentetic Algorithms + Data Structures= Evolution Programs, Springer, 2001.
Morrison, S.J., “Quality engineering design,” Journal of Manufacturing Engineer , Vol.80, No.3, pp.110-112, 2001.
Mulholland, A.J., Alvarez-Arenas, T.G., Hayward, G. and Gomatam, J., “A renormalisation approach to wave propagation in 0-3/3-3 connectivity composites,” Proceedings, Ultrasonics Symposium, Vol.2, pp.961-964, 1999.
Okamoto, S., Oguchi, K. and Sato, K., “Network architecture for optical path transport networks,” Journal of Communications, Vol.45, No.8, pp.968-977, 1997.
Owens A.J., “Process modeling and control using a single neural network,” Journal of Information and Technology, Vol.2, pp.1475-1480, 1994.
Phadke, M.S., Quality engineering using robust design, Prentice Hall, Inc., Englewood Cliffs, New Jersey, 1989.
Sen, P., “Communicating preferences in multiple-criteria decision-making: the role of the designer,” Journal of Engineering Design, Vol.12, No.1, pp.15-24, 2001.
Siah, E.S., Ooi, B.L., Kooi, P.S., and Xhou, X.D., “Experimental investigation of several novel fractal antennas-variants of the Sierpinski Gasket and introducing fractal FSS screens,” Proceedings, Microwave Conference, Asia Pacific, Vol.1, pp.170-173, 1999.
Song, C.T.P., Hall, P.S., Ghafouri-Shiraz, H., and Henning, I., “Fractal antenna research at University of Birmingham,” Proceedings, Eleventh International Conference, Vol.2, pp.724-727, 2001.
Whitley, D., Foundations of Genetic Algorithms, Morgan, 1993.