現今全球面板之需求量與日俱增，而近年來在台灣政府大力栽培下，更使台灣面板產業蓬勃發展，然而TFT產業涉及大量生產與高原料成本問題，且需求變異大，因此需要不同於以往少樣多量的製造模式。傳統之製造流程不外乎推式系統或拉式系統，推式系統雖具有高服務水準之優點，卻易造成高存貨成本之壓力；而拉式系統雖可減少存貨造成之風險，但較長的前置時間則會降低其服務水準。本研究結合了推式與拉式系統優點之推拉系統，其可同時解決服務水準與存貨成本之衝突。因此若我們能找出一適當的推拉界限，則可以同時改善上兩目標。本研究將結合系統模擬和反應曲面法，探討如何在生產情形為隨機狀態且生產多種產品之生產線中，找出適合之可控因子及其推拉界限位置，以決定適合之推拉系統架構，藉此達成提升服務水準並降低總存貨成本之目的。最後，結合一面板廠之實際案例來驗證本研究。

The demand for flat-screen monitor panels increases each day. With the help of the Taiwanese Government’s heavy input and guidance, the Taiwanese flat panel industry flourishes. However, the TFT industry faces the problems of mass production and high material cost, as well as high demand variability, thus a different production model is required as opposed to the traditional way of low-variety high-volume production. The traditional production process involves either the push system or the pull system. Although the push system has the advantage of high service level, it has the disadvantage of pressure from possible high inventory cost. On the contrary, the pull system could minimise the risk of inventory, but it has the aspect of prolonged lead time which could compromise the level of service. This study investigated the push/pull system which combined the advantages of both the push system and the pull system, a solution to the conflict between service level and inventory cost. With the approach of combining the system Simulation and response surface analysis, this study aimed to investigate, under situations of stochastic process and multiple production lines, a suitable control factor and its related push/pull boundary positions. By doing so, a suitable framework for the push/pull system could be established, thus the goal to lower overall inventory cost and improvement of service could be accomplished. A case study of a TFT-LCD factory is included to test the theories investigated in this study.

參考文獻
朱延智，（民92），產業分析，五南圖書出版股份有限公司，台北。
余朝權，（民80），產業分析構面之探討，台北市銀行月刊，第二十二卷，第七期，頁9-19。
產業技術知識服務計畫（ITIS）智網，（民95），Available: http://www.itis.org.tw/pubinfo-detail.screen?pubid=69831434
陳文哲，（民70），看板方式實務，中興管理顧問公司，台北。
曾珞萍，（民89），以反應曲面法尋找多目標模擬模式之最佳解－以半導體封裝廠印字區為例，國立成功大學製造工程研究所，碩士論文。
經濟部技術處，（民91），TFT-LCD產業之競合與經營型態分析，工業技術研究院，新竹。
黎正中，陳源樹，（民95），實驗設計與分析，高立圖書有限公司，台北。
Box, G.E.P., and Behnken, D.W., 1960, Some new three level designs for the study of quantitative variables, Technometrics, 2, 455-475.
Box, G.E.P., and Wilson, K.B., 1951, On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, 13, 1-45.
Brown, A.O., Lee, H.L., and Petrakian, R., 2000, Xilinx improves its semiconductor supply chain using product and process postponement, Interfaces, 30, 65-80.
Buzacott, J. A., and J. Shanthikumar G., 1993, Stochastic Models of Manufacturing Systems, Prentice Hall Inc., Englewood Cliffs, NJ.
Chang, T.M., and Yih, Y., 1994, Generic Kanban systems for dynamic environments, International Journal of Production Research, 32, 889-902.
Cheng, T.C.E., and Podolsky, S., 1993, Just-in-time manufacturing: an introduction, 2nd edition, Springer, New York.
Cochran, J.K., and Kim, S.S., 1998, Optimum junction point location and inventory levels in serial hybrid push/pull production systems, International Journal of Production Research, 36, 1141-155.
Deosthali, P., and Gardel, A., 1990, Using simulation in semiconductor fabrication, Advanced semiconductor manufacturing Conference and Workshop, 22-26.
Derringer, G., and Suich R., 1980, Simultaneous optimization of several response variables, Journal of Quality Technology, 12, 214-219.
Donk, P.V.D., 2001, Make to stock or make to order: the decoupling point in the food processing industries, International Journal of Production Economics, 69, 297-306.
Fisher, M.L.,1997, What is the right supply chain for your product, Harvard Business Review, 75, 105-116.
Giovanni, M., 1983, Response surface methodology and product optimization, Food Technology, 12, 41-45.
Hall, R.W., 1981, Driving the Productivity Machine: Production Planning and Control in Japan, American Production and Inventory Control Society, Alexandria.
Hopp, W.J., and Roof, M.L., 1998, Setting WIP levels with statistical throughput control (STC) in CONWIP production lines, International Journal of Production Research, 36, 867-882.
Kanet, J.J., 1988, MRP 96: time to rethink manufacturing logistics, Production and Inventory Management Journal, 29, 57-61.
Kelton, W.D., Sadowski, R.P., Sadowski, and Deborah, A., 2007, Simulation with Arena, McGraw-Hill, New York.
Lee, H.L., 2002, Aligning supply chain strategies with product uncertainties, California Management Review, 44, 105-119.
Liberopoulos, G., and Dallery, Y., 2000, A unified framework for pull control mechanisms in multi-stage manufacturing systems, Annals of Operations Research, 93, 325-355.
Monden, Y., 1983, Toyota Production System: Practical Approach to Management, GA: Industrial Engineers and Management Press.
Montgomery, D.C., 2005, Design and Analysis of Experiments, 6th edition, John Wiley & Sons, New York.
Noguera, J.H., and Watson, E.F., 2006, Response surface analysis of a multi-product batch processing facility using a simulation metamodel, International Journal of Production Economics, 102, 333-334
Olhager, J., 2003, Strategic positioning of the order penetration point, International Journal of Production Economics, 85, 319-329.
Olhager, J., and Ostlund, B., 1990, An integrated push-pull manufacturing strategy, European Journal of Operational Research, 45, 135-142.
Pierreval, H., and Tautou, L., 1997, Using evolutionary algorithms and simulation for the optimization of manufacturing systems, IIE Transactions, 29, 181-189.
Razmi, J., Rahnejat, H., and Khan, M.K., 1998, Use of analytic hierarchy process approach in classification of push, pull and hybrid push-pull systems for production planning, International Journal of Operations and Production Management, 18, 1134-1151.
Spearman, M.L., and Zazanis, M.A., 1992, Push and pull production systems: issues and comparisons, Operations Research, 40, 521-532.
Spearman, M.L., Woodruff, D.L., and Hopp, W.J., 1990, CONWIP: a pull alternative to kanban, International Journal of Production Research, 28, 879-894.
Taylor, L.J., 1999, A simulation study of WIP inventory drive systems and their effect on financial measurements, Integrated Manufacturing Systems, 10, 306-315.
Viswanadham, N., and Raghavan, N.R.S., 2000, Performance analysis and design of supply chains: a Petri net approach, Journal of the Operational Research Society, 51, 1158-1169.
Xiong, G., and Nyberg, T.R., 2000, Push/pull production plan and schedule used in modern refinery CIMS, Robotics and Computer Integrated Manufacturing, 16, 397-410.
Yang, T., and Tseng, L.P., 2002, Solving a multi-objective simulation model using a hybrid response surface method and a lexicographical goal programming approach—a case study on integrated circuit ink-marking machines, Journal of the Operational Research Society, 53, 211-221.
Yang, T., Kuo, Y., and Chou, P., 2005, Solving a multiresponse simulation problem using dual response system and scatter search method, Simulation Modelling Practice and Theory, 13, 356-369.