臺灣博碩士論文加值系統

　　在日常生活中以及工作環境中，往往要面對許多的決策問題，其中部分則是需要在已知方案中選出最適的方案決策，而在比較決策方案間優劣時，總需要在數個相互衝突的準則下針對所有的方案做評估，此類即為多屬性決策問題。本論文提出一多屬性決策方法-灰關聯分析方法來解決此類的問題，並結合主成份分析、模糊方法、信號雜音比與層級分析等方法來探討其分析效益。本研究共探討三個案例，第一，以製造流程系統的半導體封裝廠印字區案例，探討各因子水準情況下的田口直交表實驗，尋求多目標模擬模式的最佳解；第二，整合物流、金流與資訊流等管理與技術服務的第四方物流（4PL）供應鏈系統，在此架構下利用灰關聯分析方法來解決第三方物流（3PL）供應商的選擇問題；第三，以及半導體封裝廠設施佈置的案例，以量化與定性的屬性評估工廠可能佈置的方案，以三個應用案例作為灰關聯分析研究對象，探討灰關聯分析方法適用於不同情境與結合方法的效益。研究結果指出灰關聯分析方法能有效並明確的提供結果，並做為決策者參考的依據。

　　In daily life and working environment, there are a lot of decision making questions, and some of them need to select the most suitable alternatives decision-making in the known plan. But when compares the decision-making good and bad, always need to asses to all plans under criterion, this type is Multiple Attribute Decision Analysis. The essay brings up Multiple Attribute Decision Making Problem-Grey Relational Analysis Method to solve this question, and uses Grey Relational combination of Principal Component Analysis (PCA), fuzzy method, Single-to-Noise ratio (SN) and Analytic Hierarchy Process (AHP) to probe into the analysis of benefit. This study takes the making driftage system of semiconductor casing factory for a case, probe into the factor level under a situation at Taguchi Orthogonal Arrays experiment, and seek the most answer of simulation model in many targets; combines the logistics, gold flow and information flow in Fourth Party Logistics(4PL) supply chain system of management and technological services, uses the Grey Relational Analysis Method to solve Third Party Logistics(3PL) supply owner of choice under this structure; takes the facility arrangement in the semiconductor casing factory for a case, an attribute factory with quantification and qualitative maybe furnish the plan, regard three application cases as Grey Relational Analysis Method research object, probes into Grey Relational Analysis Method applying to different situation and benefit of the combination method. The result of study points out offering result for Grey Relational Analysis Method that can be effective and clear, and provides the reference for policymaker.

摘 要 i
Abstract ii
誌 謝 iv
目 錄 v
圖 目 錄 viii
表 目 錄 ix
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究流程 4
1.5 論文架構 5
第二章 文獻探討 6
2.1 灰關聯分析方法相關文獻 6
2.1.1 灰關聯生成 6
2.1.2 辨識係數 9
2.1.3 灰關聯係數 10
2.1.4 修正模型 11
2.2 灰關聯結合方法之相關文獻 12
2.2.1 主成份結合灰關聯分析方法 12
2.2.2 灰關聯結合模糊方法 13
2.2.3 灰關聯結合AHP方法 13
2.2.4 其它應用方法相關文獻 13
第三章 研究方法 15
3.1 灰關聯分析方法 15
3.1.1 灰關聯生成 16
3.1.2 計算Δ0i(k)、Δmin、Δmax之值 18
3.1.3 設定辨識係數ζ之值 18
3.1.4 求出灰關聯係數 19
3.1.5 求出灰關聯度與排序 20
3.2 主成份分析結合灰關聯分析方法 20
3.2.2 利用直交表規劃實驗 22
3.2.3 灰關聯生成與求取主成份得點 22
3.2.4 求取灰關聯係數、灰關聯度與找出最佳水準組合 25
3.3 灰關聯分析結合模糊方法 26
3.3.1 定義最佳與最差參考序列與灰關聯分析 27
3.3.2 模糊轉換函數 28
3.3.3 找出最佳因子組合 31
3.4 灰關聯分析結合AHP方法 31
3.4.1 灰關聯分析 32
3.4.2 使用AHP屬性權重 33
第四章 實驗分析 36
4.1 半導體封裝廠印字區案例 36
4.1.1 案例說明 36
4.1.2 灰關聯生成與係數的模式比較 40
4.1.3 灰關聯結合主成份分析方法 51
4.1.4 灰關聯結合模糊方法 57
4.1.5 灰關聯結合信號雜音比分析方法 65
4.1.6 各實驗比較 71
4.2 3PL供應商的選擇 73
4.2.1 案例說明 73
4.2.2 3PL供應商的灰關聯分析 75
4.2.3 以AHP決定屬性權重結合灰關聯分析 79
4.3 半導體封裝廠設施佈置 83
4.3.1 案例說明 83
4.3.2 設施佈置方案的灰關聯分析 86
4.3.3 灰關聯與資料包絡法、順序偏好法比較 91
第五章 結論與建議 93
5.1 結論 93
5.2 建議與未來研究 94
參考文獻 95
附錄A 98
附錄B 105

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