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研究生:陳建光
研究生(外文):Chen, Chien-Kuang
論文名稱:整合策略層級與作業層級之供應鏈模式
論文名稱(外文):A Synchronized Model Considering the Strategic and Operational Levels in the Supply Chain
指導教授:陳飛龍陳飛龍引用關係
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:89
中文關鍵詞:供應鏈模式
外文關鍵詞:Supply Chain Managementsynchronized model
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這幾年來,整個市場上的供需環境有相當大的轉變,因此供應鏈管理在業界掀起了一股熱潮。由於許多大型資訊系統的發展,使得收集系統中各類即時資訊的技術逐漸達到成熟的階段,而如何有效的透過這些資訊,來輔助企業進行決策,便成了企業強化其競爭力的關鍵點。隨著供應鏈管理這個議題在業界所受到的重視,過去也有相當數量的研究,然而,在過去的相關研究中,極大多數是針對其中各項議題分別做探討,缺乏對此議題整體的討論。
此外,企業現行決定系統成員結構(configuration)的方式一般皆是僅由供應鏈模式中的策略層級來進行考量。但是在此情況下,所採用的輸入資料是參考“歷史資料”或是由“其他供應鏈環境下相關的數據”所估計而來的,相較之下,便會降低對於本身問題的適用性。而且一般來說,由於在做完決策之後,往往欠缺一個有效率的系統化方法回過頭來對上次決策結果的效能做分析。因此,最常見的狀況就是企業會依照之前決策結果所訂定的系統成員結構繼續運作下去。如此一來,常使整個供應鏈系統無形中默默地負擔了許多不必要的成本。
本研究就是針對上述的不足所提出,所採用的方式為:藉由將作業層模式所產出之變動成本回傳至策略層模式中,去對那些之前在執行一項策略規劃時,僅透過其他系統環境所取得或是其他較不合適的輸入值做調整的動作。如此,將傳統供應鏈模式中的這兩個層級同時納入考量,並以模式產出之最終結果提供給決策者作為決定下次系統成員結構的參考依據,以利整個系統達到成本最小化的目標。最後,藉由一實例說明來對本研究所提出之模式進行驗證,除了說明此模式之運用方式之外,並從總系統成本的角度來評估各個控制參數變化對本模式所造成的影響,最後透過結果分析結論出本模式具相當程度之可行性。

In the past, a majority of the previous research put their focuses only on the individual part of the supply chain system. Rectifying such a situation by proposing a synthetic model, which combined the strategic and operational planning level, is the primary purpose of this research.
For this synchronized model, it considers supply chain as a centralized system where there is a global coordinator in charge. The objective function is to minimize the total cost of this system with a certain desired customer service level satisfied, which may be determined depending on the differences of market environment and the policy maker’s preferences. Moreover, the following components tackle the related issues in the operational planning level: raw material management analysis, production and final product stockpile analysis and distribution analysis. Through the seamless integration of these sub-models, incorporating the model of strategic planning level, this framework captures the behaviors of supply chain appropriately and also facilitates the decision making process.
Finally, a numerical example is illustrated to demonstrate the applicability and the effectiveness of the synchronized model, and the sensitivity analysis is also applied. The results show that the proposed model is applicable and capable of assisting the decision maker in designing the supply chain network.

Abstract I
Abstract (Chinese) II
Acknowledgements III
CONTENTS IV
LIST OF FIGURES VI
LIST OF TABLES VII
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation 5
1.3 Research objective 8
1.4 Research approach and organization 9
Chapter 2 Literature review 11
2.1 Introduction to supply chain management 11
2.1.1 Definition of supply chain 11
2.1.2 Definition and evolution of supply chain management 13
2.1.3 The bullwhip effect 16
2.2 Hierarchy of supply chain systems 18
2.2.1 The planning levels in supply chain 18
2.2.2 Supply chain levels in modeling 19
2.2.3 Measures of supply chain performance 22
2.3 Simulation modeling 26
2.3.1 The essence of simulation 26
2.3.2 Simulation models 27
2.3.3 The deficiencies of simulation modeling applied to supply chain 29
2.4 Optimization modeling 30
2.4.1 Deterministic analytical models 31
2.4.2 Stochastic analytical models 34
2.4.3 Other model types and solutions 36
2.5 Literature summary 37
Chapter 3 Formulation of the synchronized supply chain model 43
3.1 The model and its properties 43
3.2 Model structure and formulation 46
3.2.1 Assumptions and notation 46
3.2.2 The sub—model of strategic planning level 49
3.2.3 The sub—model of operational planning level 52
3.3 Model illustration 61
3.3.1 Illustration of the strategic level sub-model 62
3.3.2 Illustration of the operational level sub-model 62
3.3.3 The procedure of computation 64
Chapter 4 Numerical illustration and results analysis 67
4.1 Problem descriptions 68
4.2 Sensitivity analysis 69
4.2.1 Computational results 69
4.2.2 Model analysis 73
4.2.3 Further discussions 78
4.3 Summary 80
Chapter 5 Conclusions and future research 82
5.1 Conclusions 82
5.2 Directions for future research 83
References 84
Appendix A Appendix to Chapter 3 88

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