Responsive image
博碩士論文 etd-0825110-052117 詳細資訊
Title page for etd-0825110-052117
A Study on collaborative forecasting mechanism for artificial leather industry in Taiwan
Year, semester
Number of pages
Yi-min Tu
Advisory Committee
Shan-jhong chao
Date of Exam
Date of Submission
Collaborative business, Supply chain management, CCU, Artificial leather industry, Process simulation
本論文已被瀏覽 5769 次,被下載 14
The thesis/dissertation has been browsed 5769 times, has been downloaded 14 times.
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.
目次 Table of Contents
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
參考文獻 References
1. Aviv, Y. (2001). The effect of collaborative forecasting on supply chain performance. Management Science, 47(10), 1326-1343.
2. Aviv, Y. (2007). On the benefits of collaborative forecasting partnerships between retailers and manufacturers. Management Science, 53(5), 777.
3. Baker, K. R. (1974). Introduction to sequencing and scheduling John Wiley & Sons.
4. Ball, M., Chen, C. Y., & Zhao, Z. (2003). Optimization based available to promise.
5. Ball, M. O., Chen, C. Y., & Zhao, Z. Y. (2004). Available to promise. INTERNATIONAL SERIES IN OPERATIONS RESEARCH AND MANAGEMENT SCIENCE, , 447-558.
6. Ballou, R. H., Gilbert, S. M., & Mukherjee, A. (2000). New managerial challenges from supply chain opportunities. Industrial Marketing Management, 29(1), 7-18.
7. Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032-1048.
8. Cederlund, J. P., Kohli, R., Sherer, S. A., & Yao, Y. (2007). How motorola put CPFR into action. Supply Chain Management Review, 11(7), 28-35.
9. Chen, F., Drezner, Z., Ryan, J. K., Simchi-Levi, D. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science, 46(3), 436-443.
10. Chen, J. H., Lin, J. T., & Wu, Y. S. Order promising rolling planning with ATP/CTP reallocation mechanism.
11. Chopra, S., & Meindl, P. (2007). Supply chain management. strategy, planning & operation. Das Summa Summarum Des Management, , 265-275.
12. Christopher, M. (1999). Logistics and supply chain management: Strategies for reducing cost and improving service. International Journal of Logistics Research and Applications, 2(1), 103-104.
13. Christopher, M. (2005). Logistics and supply chain management: Creating value-added networks Pearson education.
14. Coase, R. (1937). The nature of the firm. Economica, 4(16), 386-405.
15. Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply chain management: More than a new name for logistics. The International Journal of Logistics Management, 8(1), 1-14.
16. Davis, T. (1993). Effective supply chain management. Sloan Management Review,
17. Disney, S., & Towill, D. (2003). The effect of vendor managed inventory (VMI) dynamics on the bullwhip effect in supply chains. International Journal of Production Economics, 85(2), 199-215.
18. Fliedner, G. (2003). CPFR: An emerging supply chain tool. Industrial Management and Data Systems, 103(1), 14-21.
19. Forrester, J. W., & Wright, J. (1961). Industrial dynamics MIT press Cambridge, MA.
20. Frankel, R., Goldsby, T. J., & Whipple, J. M. (2002). Grocery industry collaboration in the wake of ECR. International Journal of Logistics Management, 13(1), 57-72.
21. Fredendall, L., & Lea, B. (1997). Improving the product mix heuristic in the theory of constraints. International Journal of Production Research, 35(6), 1535-1544.
22. Glassey, C. R., & Resende, M. G. C. (1988). Closed-loop job release control for VLSI circuit manufacturing. IEEE Transactions on Semiconductor Manufacturing, 1(1), 36-46.
23. Glassey, C. R., & Weng, W. W. (1991). Dynamic batching heuristic for simultaneous processing. IEEE Transactions on Semiconductor Manufacturing, 4(2), 77-82.
24. Gunasekaran, A., & Ngai, E. (2004). Information systems in supply chain integration and management. European Journal of Operational Research, 159(2), 269-295.
25. Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), 333-347.
26. Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations and Production Management, 21(1/2), 71-87.
27. Gupta, A. K., & Sivakumar, A. I. (2006). Job shop scheduling techniques in semiconductor manufacturing. The International Journal of Advanced Manufacturing Technology, 27(11), 1163-1169.
28. Ho, H. (2005). A study of establishing the order promising process based on allocated ATP.
29. Janssen, M., Laflamme-Mayer, M., & Stuart, P. Survey of data management systems used in the pulp and paper industry. FOCAPO 2003: Proceedings Foundations of Computer Aided Process Operations, , 551-554.
30. Jeong, B., Sim, S. B., Jeong, H. S., & Kim, S. W. (2002). An available-to-promise system for TFT LCD manufacturing in supply chain. Computers & Industrial Engineering, 43(1-2), 191-212.
31. Johnson, M. (1999). Collaboration data modeling: CPFR implementation guidelines. 1999 Annual Conference Proceedings of the Council of Logistics Management, Syncra Systems Inc., One Cambridge Center Cambridge, MA, , 2142
32. Kelton, W. D., Sadowski, R. P., & Sturrock, D. T. (2003). Simulation with ARENA McGraw-Hill Science Engineering.
33. Knolmayer, G., Mertens, P., & Zeier, A. (2002). Supply chain management based on SAP systems: Order management in manufacturing companies Springer Verlag.
34. Kopczak, L. R., & Johnson, M. E. (2003). The supply-chain management effect. MIT Sloan Management Review, 44(3), 27-34.
35. Krajewski, L. J., & Ritzman, L. P. (2005). Operations management:Process and value chains Pearson.
36. Kung, K. H. (2002). A study of business process design based on the functional mechanism in SCM to improve the competitive advantages for the domestic OEM manufacturers in the electronical industries.
37. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558.
39. McCarthy, T. M., & Golicic, S. L. (2002). Implementing collaborative forecasting to improve supply chain performance. Management, 32(6), 431-454.
40. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., et al. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1-26.
41. Metters, R. (1997). Quantifying the bullwhip effect in supply chains. Journal of Operations Management, 15(2), 89-100.
42. Nurmi, D., Mandal, A., Brevik, J., Koelbel, C., Wolski, R., & Kennedy, K. (2006). Evaluation of a workflow scheduler using integrated performance modelling and batch queue wait time prediction. Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, 119.
43. Parks, L. (1999). CPFR programs facilitate inventory management. Drug Store News, 21(2), 27.
44. Porter, M. E. (1980). Industry structure and competitive strategy: Keys to profitability. Financial Analysts Journal, 36(4), 30-41.
45. Qasem, A., Kennedy, K., & Mellor-Crummey, J. (2006). Automatic tuning of whole applications using direct search and a performance-based transformation system. The Journal of Supercomputing, 36(2), 183-196.
46. Selladurai, V., Aravindan, P., Ponnambalam, S., & Gunasekaran, A. (1995). Dynamic simulation of job shop scheduling for optimal performance. International Journal of Operations and Production Management, 15, 106-106.
47. Shu, Y. H. (2008). TOC based research on the FPC industry's improvement through ATP/CTP production and marketing mechanism.
48. Smaros, J. (2003). Collaborative forecasting: A selection of practical approaches. International Journal of Logistics Research and Applications, 6(4), 245-258.
49. Stadtler, H., & Kilger, C. (2007). Supply chain management and advanced planning: Concepts, models, software, and case studies Springer Verlag.
50. Stank, T. P., Daugherty, P. J., & Autry, C. W. (1999). Collaborative planning: Supporting automatic replenishment programs. Supply Chain Management: An International Journal, 4(2), 75-85.
51. Sterman, J. D. (1989). Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Science, 35(3), 321-339.
52. Sterman, J. D., & Off, D. T. T. (1992). Flight simulators for management education. OR/MS Today, 19(5), 40-44.
53. Tatsiopoulos, I., Panayiotou, N., & Ponis, S. (2002). A modelling and evaluation methodology for E-commerce enabled BPR. Computers in Industry, 49(1), 107-121.
54. Wu, C. (2004). A study of collaborative forecasting mechanism for panel maker in taiwan TFT-LCD industry.
55. Xiong, M., Tor, S. B., Khoo, L. P., & Chen, C. H. (2003). A web-enhanced dynamic BOM-based available-to-promise system. International Journal of Production Economics, 84(2), 133-147.
56. Zhao, X., Xie, J., & Leung, J. (2002). The impacts of forecasting model selection on the value of information sharing in a supply chain. European Journal of Operational Research, 142(2), 321-344.
57. chemyq-化工引擎Transfer coating-轉移塗佈。
58. Chen, Y. C. (2001). 台灣產業因應供應鏈管理與全球運籌現況之對策. 2001 年科技與管理學術研討會論文集,
59. Fan, N. T. (2005). 協同規劃, 預測及補貨與即時採購於製造績效增進之研究.
60. FangHua Leather Machine Co., Ltd. Dry PU/PVC transfer coating line-
乾式聚氨脂/氯乙烯轉移塗佈產線 Retrieved from
61. Hsieh, W. J.(2002)。即時接單回應機制下後向耗用期間與確認範圍大小二者關係之研究。
62. STRATEGIES, A. S. C. 反應型供應鏈與預測型供應鏈策略績效之評估. Taiwan, T.
63. Wang, C. A. (2003). 供應商參與協同設計的動機與參與程度之研究.
64. 丁志宏, 鄧紹綱, 劉延良, & 關鍵字. 導入 CPFR 系統關鍵成功因素之研究.
65. 且OhSlun, K. CM (l, 1) 模型預測高雄港貨櫃吞吐量.
66. 俞洪亮, & 黃建勝. 製造商之採購管理行為對採購風險及生產績效之影響.
67. 劉賓陽. (2004). 供應商控管存貨機制於動態需求型態下之決策因素互動分析
68. 以國內光電產業之中游面板廠為研究對象.
69. 劉賓陽. (2006). 作業研究.
70. 呂博裕, & 林凱莉. 高訂單達交率下石英製品再製造系統之模擬研究.
71. 屠益民(2000)。動態流程設計方法之研究。
72. 巫沛倉, 王心怡, & 朱蓮春. 在不完全供貨之下零售商存貨 在不完全供貨之下
73. 零售商存貨策略之探討-以 QR 模式為例.
74. 廖明鈺. (2009). 台灣製鞋產業之競爭策略-以寶成工業股份有限公司為例.
75. 張人偉. (2006). 事件驅動之訂單組合排程法: 以半導體製造為例 An event.
76. 張谷光, & 王福琨. 應用六標準差手法提昇 CPFR 之效益.
77. 曾建榮. 三芳化工: 沒有研發, 就沒有將來!, 技術尖兵第 083 期 90 年 11 月號-[科技論壇](傑出獎) www. Ita.Org,
78. 李波, & 楊淑娟. (2005). 皮革機械加工原理.
79. 林我聰, 陳寬茂, & 曾永勝. CPFR 流程下之訂單預測方法. 協同商務價值鍊之經營控管實務研討會論文摘要集, , 11-11.
80. 王怡強. (2007). 訂單承諾之資訊分享及其誤差對供應鏈成本影響之評估.
81. 王立志. (1999). 系統化運籌與供應鏈管理. 台北市: 滄海書局, , 27-33.
82. 研究生, 吳慧玲, & 蕭瑞祥. 關鍵字: 協同規劃預測補貨 (CPFR), 零售業, 百貨量販業, 烘焙業.
83. 連書賢, 張明, & 宗博士. 運動鞋產業垂直分工之起源.
84. 藍俊雄, & 周信甫. 光電產品預測之研究: 以 LED 為例.
85. 邱漢郎. (2006). 臺灣人工皮革產業與新產品的進入策略.
86. 陳穆臻, 張舜傑, & 陳仕明. 製造商與供應商之協同規劃運作.
電子全文 Fulltext
論文使用權限 Thesis access permission:校內公開,校外永不公開 restricted
開放時間 Available:
校內 Campus:開放下載的時間 available 2010-08-25
校外 Off-campus:永不公開 not available

您的 IP(校外) 位址是
論文開放下載的時間是 校外不公開

Your IP address is
This thesis will be available to you on Indicate off-campus access is not available.

QR Code