本課程為本系研究所選修課程，主要在於介紹工業設計研究領域，所採用的各項設計方法，內容涵蓋計量、統計、邏輯概念、設計決策的推演、設計策略與規劃…等，課程上，藉由設計方法手段，而達成最佳化的決策，使得設計不再僅是天馬行空的概念，而能夠具體呈現與成效。授課上，並輔以相關程式設計說明與計量軟體應用，使研究生得以在日後研究論文寫作階段，得以瞭解與學習在工業設計領域所需的各項設計方法與決策手段，提供相關的研究應用。This course is an elective course for this department. It mainly introduces the field of industrial design research and various design methods used. The content covers measurement, statistics, logical concepts, deduction of design decisions, design strategies and planning... etc. The course, Through design methods and means, optimal decisions are achieved, so that design is no longer just a fantasy concept, but can be concretely presented and effective. The lectures are supplemented by relevant programming instructions and measurement software applications, so that graduate students can understand and learn various design methods and decision-making methods required in the field of industrial design and provide relevant research applications in the future writing stage of research papers.
1.Kai Yang and Basem S EI-Haik, Design for Six Sigma: A Roadmap for Product Development, 2nd Eds, McGraw-Hill, 2009.
2.Ali, K. Kamrani, Saed M. Salhieh, Product Design for Modularity, Kluwer Academic Publisher, 2002.
3.Skvarcius, R. and Robinson, W.B., Discrete Mathematics with Computer Science Applications, 1986.
4.李允中、王小蟠、蘇木春，模糊理論及其應用，全華，2003.
5.蘇木春、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，2000.
6.Chapman, S.J., Matlab Programming for Engineers, Thomson, 2008.
1.Kai Yang and Basem S EI-Haik, Design for Six Sigma: A Roadmap for Product Development, 2nd Eds, McGraw-Hill, 2009.
2.Ali, K. Kamrani, Saed M. Salhieh, Product Design for Modularity, Kluwer Academic Publisher, 2002.
3.Skvarcius, R. and Robinson, W.B., Discrete Mathematics with Computer Science Applications, 1986.
4. Li Yunzhong, Wang Xiaopan, Su Muchun, Fuzzy Theory and Its Application, Quanhua, 2003.
5. Su Muchun, Zhang Xiaode, machine learning, neural networks, fuzzy systems and genetic algorithm principles, Quanhua, 2000.
6.Chapman, S.J., Matlab Programming for Engineers, Thomson, 2008.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時作業平時作業 Daily homework |
40 | 包括10次平時作業（選取8次成績最高計算） |
| 學習態度與出席率學習態度與出席率 Learning attitude and attendance rate |
15 | 點名15次，每次1分計算 |
| 期中論文研讀、報告發表期中論文研讀、報告發表 Midterm paper reading and report publishing |
15 | 相關案例的報告發表 |
