臺灣博碩士論文加值系統

在供應鏈的體系中,由於資訊的透通度不佳以及資訊的延遲進而導致訂單資
訊被擴大甚至於扭曲的現象成為長鞭效應,在這樣的情形下,製造商以及上游供 應商將會產生庫存波動加大或是生產計畫不穩定等影響;然而上游的供應產生問 題將會連帶影響下游採購成本的變化,因此若企業只考量自身利益將無法合適的 在這個時代生存,而供應鏈的協同運作就是供應鏈中的成員為了共同利益的目標 而產生的。

而本研究將以供應鏈中之製造商為運籌中心,探討供應鏈的協同運作模式下, 資訊透通度提高並且進而協同預測、規劃等模式下對於供應鏈長鞭效應問題改善 的效益。本研究以台灣人工皮革產業為供應鏈的研究目標,藉由流程模擬以及改 良等模式,並且以 Arena 流程模擬軟體進行分析,了解於不同的需求情境以及上 下游突發狀況下,對於現況以及導入協同商務機制之供應鏈績效改善,其結果可 以提供台灣人工皮革產業未來導入協同商務運作模式之參考依據。

The bullwhip effect is known as a phenomenon of information distortion due to the lack of information sharing and the forecast error. This phenomenon could cause the productions plan to be instable and the inventory fluctuation among the supply chain members. Those situations above will also cause the fluctuation of purchasing costs to downstream members. The raising costs and inefficiency will be the burden of whole supply chain and not single party can exempts such result. Therefore, the collaboration of supply chain members is aim to solve such problems.
In this study, we set the manufacturer as the logistic center among supply chain members, and operate the collaborative business. The artificial leather industry in Taiwan will be the platform of this study. Operation models will be built by the classical type, CPFR type, and CCU (collaborative and coordinative unit) type, and also to be simulated to analyze the performances through several KPIs. The result of this study can be the reference when adopting CPFR or CCU into Taiwan artificial leather industry.

摘 要 4
Abstract 5
Table of Contents 6
List of Figures 8
List of Tables 12
Chapter One Introduction 13
Chapter Two Literature Review 19
2.1 Supply chain management and ATP / CTP mechanism 19
2.2 Collaborative Planning, Forecasting and Replenishment 22
2.3 Coordinating and Collaborative Unit (CCU) 26
2.4 Vertical integration 31
Chapter Three Research Design 32
3.1 Industry Background 32
3.2 Bullwhip effect in supply chain 33
3.3 Forecast and replenishment of the industry 34
3.4 The Beer game 38
3.5 Collaborative planning, forecasting, and replenishment 39
3.6 Coordinative and Collaborative Units (CCU) 43
3.7 Scenarios analysis 48
Chapter Four Case study and Simulation 49
4.1 The case study company A 49
4.2 Model construction 51
4.2.1 Classical model construction 56
4.2.2 CPFR model construction 60
4.2.3 CCU model construction 62
4.3 Model Validation 63
4.3.1 Conceptual validation 63
4.3.2 Operational validity 63
4.3.3 Pilot run 73
4.4 Simulation 75
4.4.1 Scenarios design 75
4.4.2 Uncertain inquiry arrivals 76
4.4.3 Pulse inserting demand arrivals 82
4.4.4 Raw material replenishment latency 88
4.4.5 Forecast error 94
4.5 Conclusion 100
Chapter Five Conclusion 101
Reference 103
Appendix A 108
a. Classical model SIMAN codes 108
b. CPFR model SIMAN codes 113
c. CCU model SIMAN codes 117

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