臺灣博碩士論文加值系統

田口方法應用品質工程精神，在提升產品品質的成效方面頗具實用價值，因此深受國內外產業界的肯定。但隨著產品的設計愈來愈複雜，產品品質的良莠問題已非最佳化單一品質特性就能解決，往往需要考慮到多品質特性的同時最佳化，而田口方法僅能解決單一品質特性最佳化的問題。若依照單一品質特性的方法對個別品質特性分別最佳化，其結果可能使品質特性間，發生相互衝突、矛盾的現象。此時只能依靠工程人員的經驗來選擇參數水準，而由於工程人員的認定標準不一致，容易產生不確定性與模糊性。針對上述問題，本研究先利用田口方法中處理單品質特性的方法，依照品質特性的特性分別計算出SN比，再將SN 比使用灰關聯生成進行數據的前處理，並藉由灰關聯係數值來建構製程參數與個別品質特性間的關係，最後結合模糊推論系統去整合多重品質特性之問題求出最佳解。本研究所提出之參數水準選取方法，用以解決品質特性間，參數水準選取結果可能產生衝突、矛盾的狀況。並將此演算模式使用MATLAB編輯成操作介面應用程式，輔助工程人員快速且正確得到製程最佳參數水準組合。為了驗證此演算模式之有效性與實用性，將實際應用於奈米碳管背光模組(Carbon Nanotube Back Light Unit, CNT-BLU)厚膜網板印刷製程(Thick-Film Screen Printing Process)，以本研究所提出之演算模式－「灰關聯模糊法」，找出最佳參數水準組合，幫助案例公司節省實驗成本，縮短新產品由實驗階段導入試量產階段的時程。

Taguchi method has been extensively used for enhancing product quality in industry. More than one quality characteristics must be simultaneously considered to effectively improve the product quality due to the increasing complexity of product design. However, Taguchi’s methodology only optimize on single quality characteristic.
Optimizing each quality characteristic separately may not result the optimality for the entire production. More often, considering one quality characteristic may conflict with the other. When the conflict exits, it is mainly resolved by the engineer's experience. Thus, the quality may not be optimized and could present the possible lost. The decisions made by the engineer are to choose the parameter levels which have the properties of uncertainty and fuzziness.
To find a feasible and effective solution for the aforementioned problem, this research first uses Taguchi method by only considering the single quality characteristic; then separately calculating the SN ratio according to the quality characteristic; then, using the obtained SN ratio and grey relation generation to conduct a pre-process on data; adopting the grey relational coefficient to construct the process parameter and the individual quality characteristic relations; finally using the fuzzy inference mechanism to find the best solution. This research proposed a parameter level selection method which solves conflicts on the selection of the quality characteristic and the parameter level. The proposed algorithm is implemented by MATLAB. To demonstrate its capability of determining the optimal parameter levels combination.
In order to show the effectiveness and practicality of the proposed algorithm, we apply this method to Carbon Nanotube Back Light Unit (CNT-BLU) Thick-Film Screen Printing Process. The results show that Grey Relation Analysis and Fuzzy Inference System can find the best production process parameter level combination. The proposed methodology can significantly reduce the cost and time on experiment during the period of new product experiment and the pilot production stage.

頁次
中文摘要 i
英文摘要 ii
致謝 iii
目錄 iv
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1研究背景 1
1.2研究動機與目的 2
1.3研究限制與範圍 3
1.4研究流程與內容 3
第二章 文獻探討 6
2.1田口式品質工程 6
2.1.1損失函數 8
2.1.2田口的品質特性 10
2.1.3影響產品或製程績效的因子 12
2.1.4直交表與線點圖 13
2.1.5田口穩健設計之步驟 13
2.2多重品質特性製程相關文獻 14
2.2.1以工程師之專業知識作判斷 14
2.2.2回歸分析模式 15
2.2.3利用訊號雜音比作分析 16
2.2.4主成份分析法 17
2.2.5多屬性決策 17
2.2.6類神經網路 18
2.2.7模糊邏輯理論 18
2.2.8灰色關聯分析 19
2.2.9多重品質特性製程最佳化之相關文獻彙整表 19
2.3本章小結 21
第三章 研究方法與模式之建構 22
3.1灰色系統理論之概論 23
3.1.1灰色關聯分析 23
3.2模糊理論之簡介 26
3.2.1模糊集合 26
3.2.2模糊推論系統架構 28
3.3研究方法小結 31
3.4模式之建構 32
3.4.1研究方法步驟與流程 32
3.4.2模式之建構與求解步驟 34
第四章 實例驗證 39
4.1奈米碳管背光模組簡介 39
4.2厚膜網印製程說明 40
4.3實驗目的與相關資料描述 40
4.3.1實驗設備與材料 41
4.3.2參數選擇 42
4.4實驗設計 43
4.5單一品質特性 44
4.6模式建構程序 46
4.7第四章小結 56
第五章 結論與建議 57
5.1結論 57
5.2 建議 58
參考文獻 59
附錄 63

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