面對市場需求快速變動下，電子產業通常設計高彈性替代料的替代關係來有效利用物料；但由於替代料決策通常採用主觀決策且決策因素中有許多不確定因素與時間性，因此本研究發展一適合動態不確定環境下決策評估模式於電子產業產品開發中替代料決策評估，此決策評估模式為結合模糊權重平均方法(Fuzzy Weight Average; FWA)與模糊推論系統(Fuzzy Inference System)之混合式系統。為求能準確評估不確定環境下之決策本研究採用模糊權重平均方法進行替代料抉擇，且為求能有效率的進行決策本研究發展一the weakest t-norm (TW)模糊權重平均方法，由於模糊計算原則上的差異，以TW準則之計算方法可直接求取各決策方案之歸屬度函數，減少以區間計算方式之複雜度，同時由於因不同決策情境下部份評估準則之模糊權重將會隨著改變。本研究以電子製造業為對象，根據替代料的價值面考量選擇了三種替代材料，並各取三家供應商來進行研究，同時應用專家知識建立模糊推論系統，於不同決策情境下將會依據專家所建立之規則變更高關聯性準則之模糊權重，以達到最適合之決策選擇。本研究設計不同面向之模擬情境，情境A是以品質為主要考量因素，情境B是以價格為主要考量因素，情境C是以交期為主要考量因素，其目的是為了瞭解在不同情境下的所產生的決策變化。於文獻中可以發現，大部分的研究都以價格、品質及交期等三項因素列為供應商選擇之重要標準。本研究並比較傳統的??cut 與TW二種計算方法，同時亦列出α水準為0.5時的模糊數來做比較；於實例分析上可以發現以TW模糊計算方法，步驟簡便且易於明瞭，且利用TW計算出來的值，其模糊量皆小於??cut 計算出來的模糊結果，相較之下，以最小模糊量之FWA方法不只保留了模糊數的原形，也提供決策者在不確定環境下較少模糊訊息的結果，對於不確定性資料能使得決策者更加能夠掌握。

Due to that the market demand is changed rapidly, the electronic industry usually designs high flexible substitutive method to efficiently utilize material. Because of the alternative material usually adopt subject decision and there are a lot of uncertain factors and the timing, the research will develop a decision support model, which may be called intelligent dynamic decision system under uncertainty, for estimating and selecting substitution in dynamic and uncertain environment. This decision evaluation model is a hybrid system combining the fuzzy weight average (FWA) with the fuzzy inference system (FIS). In order to accurately estimating the decision in uncertain environment, this research makes alternative material decision by using the FWA, and in order to making decision effectively, this research develops a model － the weakest t-norm (TW) FWA. Owing to the difference in the principle of fuzzy calculation, the weakest t-norm FWA can directly request membership function for each policy proposal and decrease the complexity in interval arithmetic method. At the same time, the fuzzy weight of some principle will be changed in different decision situation. In this paper the research also apply expert’s knowledge to build the fuzzy inference system, it will be changed the fuzzy weight of the high related criterion per expert’s rule in different decision situation. In the example of electronic industry, it found that intelligent dynamic decision system under uncertainty can present the effective policy to assist electronic industry to make substitution decision.

摘要 i
ABSTRACT iii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 ix
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究目的 5
1.4 研究架構 5
1.5 研究範圍與限制 7
1.6 研究對象與資料蒐集 7
1.7 調查問卷架構 8
第二章 文獻探討 9
2.1物料採購評估 9
2.1.1 供應商選擇 9
2.1.2 供應商評選指標 11
2.2 模糊理論 16
2.2.1 模糊集合 16
2.2.2 模糊數排序與歸屬函數 17
2.3 模糊計算 18
2.3.1 α-cut模糊算術 20
2.3.2 the weakest t-norm(TW)模糊算術 21
2.3.3 解糊化 (Defuzzication) 25
2.4 模糊權重平均 27
2.5 模糊推論系統 34
第三章 研究方法 36
3.1 研究流程 36
3.2 建立評估準則及語意變數 38
3.3 採購管理相關係數分析 44
3.4 建立專家模糊推論系統 50
3.5 建立TW模糊多準則評估模組 53
第四章 實例驗證討論與分析 56
4.1 以α-cut計算結果 56
4.2 以TW計算結果 58
4.3 比較分析α-cut與TW的評量結果 59
第五章 情境模擬分析 60
5.1 模擬假設 60
5.2 模擬情境 60
5.2.1 情境A假設 (品質) 60
5.2.2 情境B假設 (價格) 61
5.2.3 情境C假設 (交期) 61
5.3 結果分析 62
5.3.1 情境A分析 62
5.3.2 情境B分析 64
5.3.3 情境C分析 67
第六章 結論與未來研究建議 70
6.1 研究結論 70
6.2 未來研究建議 71
參考文獻 72
附錄一 採購因素評估問卷 80
附錄二 採購因素評估問卷 81

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