本研究以國內某12吋晶圓廠之自動化物料搬運系統 ( Automated Material Handling System，AMHS)為研究對象。由於半導體體製程具有複雜的加工途程及多迴流的特性，因而會造成搬運需求跟著生產變異而上下起伏變動，所以系統應適當的調派搬運車來滿足不確定性的搬運需求，避免晶舟等候過久或是搬運車阻塞，造成系統運作不佳與績效低落。
在不確定性搬運需求的架構之下，本研究將從至表(From to table)區分成搬運需求(晶舟來到率)及晶舟搬運旅次分佈比例，分別討論兩部份對於實際搬運需求量的影響。當搬運車數量不符合系統中實際需求時，將會帶給系統不良的影響，如塞車或空車運行時間過長，林(2008)提出之動態派車的概念，也的確在績效上有較佳的表現。在此架構之下，欲隨搬運需求的改變調整搬運車數，必須先預測未來的搬運需求量，也就是下個時期的晶舟搬運從至表，因此，本研究提出此資料型態因為製程及系統特性的關係，具有時間序列及非線性的特性，所以本研究改良倒傳遞神經網路，加入時間序列的特性，期望能有較好的預測效度，並結合系統模擬，除了驗證預測模式的適用性，也回饋模擬輸出，重新訓練新的預測模型，使得預測模型能保持良好的預測效度。
最後本研究以誤差量的角度，衡量以具有時間序列特性的倒傳遞神經網路決定系統中配置的車數，較傳統上以平均值配置的車數有較小的誤差，代表此方法下提供的搬運車產能較能準確的滿足該時期系統中的搬運需求量，比傳統車數配置的方法更具有可靠度。

1.王進德，類神經網路與模糊控制理論入門與應用，全華圖書股份有限公司，2008
2.林東楊，”晶圓廠自動物料搬運系統之動態車數問題”，清華大學工業工程研究所碩士論文，2008。
3.林則孟，系統模擬理論與應用，滄海書局，2001。
4.周上傑，“晶圓廠自動化物料搬運系統之派車模擬研究”，清華大學工業工程研究所碩士論文，1999。
5.吳俊寬，”晶圓廠連接式自動化物料搬運系統搬運策略之模擬研究”，清華大學工業工程研究所碩士論文，2001。
6.凌瑞賢，運輸規劃原理與實務 ，茂榮書局，2008。
7.張原銘，”晶圓廠連接式自動化物料搬運系統之模擬研究-以黃光區與盧管區為例”，清華大學工業工程研究所碩士論文，2003。
8.張婷珺，”十二吋晶圓廠自動化物料搬運系統分段式迴圈探討與分析”，成功大學製造工程研究所碩士論文，2006。
9.楊景如，”晶圓廠自動化物料搬運系統之搬運車運作策略模擬研究”，清華大學工業工程研究所碩士論文，2002。
10.廖珉鋒，”動態起訖旅次矩陣推估模型之研究”，中央大學土木工程研究所碩士論文，2000。
11.陳紹偉，“12吋IC代工廠自動化物料搬運系統之系統模擬與派工法則的研究”，台灣大學機械工程研究所碩士論文，1999。
12.陳夢倫，“積層陶瓷電容印刷製程機器參數最佳化之研究”， 國立成功大學/製造工程研究所碩士論文，1999。
13.陳惠國，張美香，“路段流量推估起迄旅次量之研究”，中華道路，第33 卷，第2 期，頁3-10，1994。
14.顏柄榮，“半導體晶圓廠自動化物料搬運系統之模擬分析”，清華大學工業工程與工程管理所碩士論文，2000。
15.Asef-Variri, Laporte, and Sriskandarajah, “The block layout shortest loop design problem”, IIE Transactions, 32, 727-734, 2000.
16.Bell M.G.H., “The Real Time Estimation of Origin-Destination Flows in the Presence of Platoon Dispersion,” Transportation Research, 25B, 115-125, 1991.
17.Brain, M., Abuzeid, S., Ph.D., “Minienvironment Technology and Automation Systems for Next Generation IC Fabs”, International Symposium on Semiconductor Manufacturing, pp.173-178, 1994.
18.Brain, M., Gould R., Kaempf, U., and Wehrung, B., “Emerging Needs for ontinuous Flow FOUP Transport”, Proceedings of the IEEE/CPMT International Electronics Manufacturing Technology (IEMT) Symposium, pp.76-82, 1999.
19.Bozer, C., and Sirinivasan, L, “Tandem configuration for automated guided vehicle system offer simplicity and flexibility”, Industrial Engineering, 21, 23-27. 1989
20.Campbell, P. L., and Laitinen, G., “Overhead Intrabay Automation and Microstocking- a Virtual Fab Case Study”, IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop, pp.368-372, 1997.
21.Chen, G., L., “Design and operation of single-loop dual-rail inter-bay material handling system”, Internation Journal of Production Research, 37, 2217-2237, 1999.
22.Chang, G. L., and Wu, J., “Recursive Estimation of Time-Varying Origin-Destination Flows from Traffic Counts in Freeway Corridors,” Transportation Research, 28B, pp.141-160, 1994.
23.Chrisos, J., Nestel-Patt, J., “Integration Risks in 300-mm Wafer Fab Automation”, Solid State Technology, Vol.41, No.7, pp.193, 196, 198, 200, 202, 1998.
24.Csatary, P., Nolan, D., Wolf, P., and Honold, A., “300mm Fab Layout and Automation Concepts”, Future Fab, Vol.1, Issue5, 1997.
25.Egbelu, P. J., ” Pull Versus Push Strategy for Automated Guided Vehicle Load Movement in a Batch Manufacturing System”, Journal of Manufacturing System, Vol.6, No.3, pp.271-280, 1987.
26.Fu, H.-S., Liao D.-Y., ”An Effective OHT Dispatching Policy for 300mm AMHS Management,” in the Proceedings of SEMICON TAIWAN 2001, Taipei, Taiwan, September 2001.
27.Hendrickson, C., McNeil, S., “Estimation of Origin-Destination Matrices with Constrained Regression”, Transportation Research, Record 976, pp.25-32, 1984.
28.Goh, B., “Back-propagation neural networks for modeling complex system,Artificial Intelligence in Engineering” 9, 143-151, 1995.
29.Graznar, J., Prasad, S., and Tata, J., “Neural network and organization system：Modeling non-linear relationships”, European Journal of Operational Research 181, 939-955, 2007.
30.Kikuchi, S., Nanda, R., and Perincherry, V., “A Method to Estimate Trip Patterns Using a Neural Network Approach”, Transporation Planning and technology, Vol.17, pp.51-65, 1992.
31.Koo, P.-H., “Estimation of Part Waiting Time and Fleet Sizing in AGV system”, The internation Journal of Flexxible Manufacturing Systems, 16, 211-228, 2005
32.Liao, D.Y., and Fu, H.S., “Dynamic OHT Allocation and in a Large-Scale, 300-mm AMHS Management”, IEEE Robotics and Automation Magazine, September, pp.22-32, 2004.
33.Lin, J. T., Wang, F. K., and Yen, P. Y., “Simulation Analysis of Dispatching Rules for an Automated Interbay Material Handling System in Wafer Fab”, International Journal of Production Research, Vol.39, No.6, pp1221-1238, 2001.
34.Lin, J. T., Wang, F. K., and Wu, C. K., “Connecting Transport AMHS in a Wafer Fab”, International Journal of Production Research, Vol. 41, No.3, pp.529-544., 2003.
35.Lin, J.T., Wang F.K., and Wu, C.K., “Simulation Analysis of the Connecting Transport of AMHS in Wafer Fab”, IEEE Transactions on Semiconductor Manufacturing, Vol.16, No.3, pp.555-564, 2003.
36.Lin, J.T., Wang F.K., and Yen, P.Y., “The Maximum Loading and the Optimal Number of Vehicles in a Double-Loop of an Interbay Material Handling System”, Production Planning and Control, Vol.15, No.3, pp.247-255, 2004.
37.Lin, J.T., Wang F.K., and Young, J.R., “Virtual Vehicle in the Connecting Transport AMHS”, International Journal of Production Research, Vol.42, No.13, pp.2599-2610, 2004.
38.Lin, J.T., Wang F.K., and Yang, C.J., “The Performance of the Number of Vehicles in a Dynamic Connecting Transport AMHS”, International Journal of Production Research, Vol.43, No.11, pp2263-2276, 2005.
39.Maxwell, W.L., and Muckstadt, J.A., “Design of Automatic Guided Vehicle Systems”, IIE Transactions, Vol.14, pp.114-124, 1982.
40.Nguyen, S., “Estimating Origin-Destination Matrices from Observed Flows,” Transportation Planning Models, Edited by Florian, M., North-Holland, pp. 363-380, 1984.
41.Kikuchi, S., Nanda, R., and Perincherry, V., “A Method to Estimate Trip Patterns Using a Neural Network Approach”, Transporation Planning and technology, Vol.17, pp.51-65, 1993.
42.Kurosaki, R., Nagao, N., Komada, H., Watanable, Y., and Yano, H., “AMHS for 300mm Wafer”, IEEE International Symposium on Semiconductor Manufacturing Conference, pp.D13-D16, 1997.
43.Rafael S.Gutierrez, Lumpy demand forecasting using neural networks,Int .J. Production Economics 111 (2008) 409-420,2007.
44.Rajotia, S., Shanker, K., and Batra, J. L., “Determination of Optimal AGV Fleet Size for an FMS”, International Journal of Production Research, Vol.36, No.5, pp.1177-1198, 1998.
45.Peters, B. A. and Yang, T., “Integrated Facility Layout and Material Handling System Design in Semiconductor Fabrication Facilities”, IEEE Transactions on Semiconductor manufacturing, Vol.10, No.3, pp.360-369, 1997.
46.Pierce, N. G., and Stafford R., “Modeling and Simulation of Material Handling for Semiconductor Wafer Fabrication”, Proceedings of the 1994 Winter Simulation Conference, pp.900-906, 1994.
47.Plata, J.J., “300 mm Fab Design-A Total Factory Perspective”,1997 IEEE International Symposium on Semiconductor Manufacturing Conference Proceedings , pp.A5-8, 1997.
48.Robillard,P., Common bus lines. Transportation Science,9, 115-121,1975.
49.Schroeder, J. P., “Automation-Centric Processing Bay Layout”, Semiconductor International, Vol.20, No.6, pp.209-10, 212, 214, 1997.
50.Schulz, M., Stanley, Timothy D., and Renelt, B., “Simulation Based Design Support for Future 300mm Automated Material Handling”, Proceeding of the 2000 Winter Simulation Conference, pp.1518-1522, 2000.
51.Tanchoco, J. M., Egbelu, P. J. and Taghaboni, F., “Determination of the total number of vehicles in an AGV-based material transport system”, Material Folw, Vol.4, pp.33-51, 1987.
52.Weiss, M., “Semiconductor Factory Automation”, Solid State Technology, Vol.39, NO.1, pp.89-90, 92, 95-96, 1996.
53.Yang, H., AKIYAMA, T., and SASAKI, T., “Estimation of time-varying origin - destination flows from traffic counts “A neural network approach”, Mathl. Comput. Modeling Vol. 27, No.9-11, pp. 323-334, 1998.