隨著積體電路尺寸不斷縮小，其製造複雜度因製程步驟增加、機台產出提升、重複回流加工 (Reentrant)、製程站點間等候時間限制縮短等因素，造成加工區內與加工區間的物流搬運量增加。自動化物料搬運系統 (AMHS) 在300mm晶圓廠中扮演重要的晶圓傳送與儲存角色，其搬運車可行駛於整廠，進行晶圓的倉儲與機台間的搬運任務。當自動化搬運系統在軌道及機台位置設計確認後，接著需考量搬運需求及搬運績效來規劃全廠搬運車數量與倉儲容量，最後再透過搬運系統之物料控制系統MCS (Material Control System) 管理搬運車之運作 (主要功能包括:即時派車、空車配置、搬運車型、路徑選擇、塞車與死鎖控制等)，以維持晶圓搬運作業。
為提高搬運系統績效，管理者在軌道設計不變及有限搬運資源條件下，通常僅能透過改善MCS搬運車控制邏輯，來縮短晶圓等候搬運車時間與傳送時間等績效。故精進MCS搬運車控制邏輯以達成降低晶圓等候搬運車時間為實務應用之重要議題。過去學者們已針對搬運車即時派車法則、路徑選擇及塞車/死鎖控制等提出許多改善方法，但對於其他改善控制器邏輯(如:空車配置)等方法較少探討。實務上，以一座大型晶圓廠為例，有數十條加工區且多達上百台搬運車運行，在生產過程中批貨須經過上百道連續加工，且回流至不同加工區的環境下，如何有效控制搬運車的空車配置，讓機台不因等候搬運車時間過久而降低機台之生產力。本研究期望提出修改MCS系統動態車數配置方法，讓搬運車資源可以快速服務晶圓；此外，當MCS在進行搬運車即時派工時，亦可允許同一站點的多批晶圓同時發出搬運需求，讓晶圓等候搬運車時間降低，達到最佳搬運績效。故提出兩項改善MCS搬運車控制策略議題，有效地降低晶圓等候搬運車時間，提高生產績效。
第一項搬運車動態車數配置控制策略，此為針對晶圓廠內不同intrabay間之搬運車數配置 (Allocation) 議題。本研究以兩條intrabay為基礎發展動態規劃車數配置方法。首先，透過分析AMHS狀態而將各個intrabay的機台等候搬運命令數與搬運車數定義為狀態變數 (State variable)，並定義狀態轉換機率與等候命令成本公式；接著，利用動態規劃系統讓等候時間成本最短條件下，產生最佳車數配置控制決策 (Control policy)；最後，利用模擬模式來驗證動態車數規劃系統方法所得到的傳送績效較現行方式佳。本研究目的為讓自動化物料搬運系統之MCS可根據系統狀態變化來動態配置搬運車，有效縮短機台等候空車時間。
第二項搬運車預派方法之搬運控制策略，此為針對晶圓廠內搬運系統之命令提前派工(Pre-dispatching)議題。首先，透過分析現行MCS即時派車系統行為之循序圖 (Sequence diagram)，找到以既有派車法則為基礎下，對同一站點之多筆搬運命令需求，提出一套提前派車方法，來改善現行一批批循序派車方法。本研究以晶圓廠爐管區加工為對象，針對高溫爐管的集批加工 (Form-batching manufacturing) 特性，提出一套提前預派搬運車動作 (Pre-dispatching vehicle)，以解決爐管機台因每次派工4-6批晶圓至機台所造成之搬運車等候時間過長問題。首先，透過現有MCS搬運命令產生邏輯流程之循序圖分析，找出改善等候搬運車過久之問題；接著，提出當機台產生集批需求時，搬運系統之MCS須同時考量當下空車水準與預派命令數量為條件，提早將多筆搬運命令同時預派給多台搬運車，讓搬運車提早移動至搬運站點，有效改善現有方法之等候時間過久問題。最後，透過模擬模式來驗證提前預派搬運車較現有方法有更佳的搬運績效。

As the increasing complexity of semiconductor manufacturing, AMHS plays an important role to deal with the transport and storage of wafer lots in a 300mm wafer fab. As the tool layout and AMHS track design was confirmed, the next phase of AMHS design is to determine the optimum number of vehicle fleet size and stocker bin capacity with refer to transport demand and performance measure request. Finally, to deploy and implement the material control system (MCS) to manage AMHS vehicle management control (e.g. vehicle dispatching, vehicle allocation, vehicle types, vehicle routing, and congestion/deadlock control) for daily operations.
In order to improve the transport performance, fab managers continuously modify MCS vehicle management method to reduce vehicle waiting time and transport time of the wafer lot. Many researchers have paid efforts to propose the approaches in vehicle dispatching, vehicle routing, and congestion or deadlock control. However, there are few researches to address the other MCS vehicle management problem, e.g. vehicle allocation control. In a large-scale wafer fab, there are many intrabays and over hundreds of vehicle moving within or between intrabays. With the uncertainty involved in wafer lot movement, dynamically allocating vehicles to each intrabay is very difficult. Furthermore, in the current vehicle dispatching system, MCS only dispatches one vehicle for one load port at a time but this method cannot reduce the vehicle waiting time for one load port which has more than two transport jobs to move by AMHS. In this dissertation, two vehicle management strategies was proposed to reduce the vehicle waiting time of the wafer lot and improve AMHS system effectiveness.
In the first study, a dynamic vehicle allocation control (DVAC) method is proposed for a connecting transport AMHS in a 300mm wafer fab. The objective is to minimize the sum of the expected long-run average transport job waiting cost. An interesting exhaustive structure in the optimal vehicle allocation control is found in accordance with the Markov decision model. Based on this exhaustive structure, an efficient algorithm is developed to solve the vehicle allocation control problem numerically. The performance of the proposed method is verified by a simulation study. Compared with other methods, the DVAC method can significantly reduce the waiting cost of wafer lots for AMHS vehicle transportation. The control policy can help fab managers to enhance MCS vehicle control logic to reduce the empty vehicle arrival time.
In the second study, a pre-dispatching vehicle (PDV) method is proposed to simultaneously call several empty vehicles to move to a load port for executing transport jobs at a time. In semiconductor manufacturing, a furnace tool has a long processing time of 6 h to 12 h, thus making its operation a form-batch manufacturing step. With this application, wafer lots are temporarily stored in stockers, and delivery to furnace tools for processing is executed when the work-in-process (WIP) level reaches four to six lots. Unlike current methods, where empty vehicles are sequentially assigned for movement to load ports, the PDV method simultaneously calls several empty vehicles to move to a load port with refer to available empty vehicles and pre-dispatching vehicle quantity. This finding is useful for fab managers to explore the possibility of applying the PDV method to other areas and to continuously reduce the vehicle waiting time of the wafer lot.

[1] Agrawal, G.K. and Heragu, S.S., (2006) A survey of automated material handling systems in 300-mm semiconductor fabs, IEEE Transactions on Semiconductor Manufacturing, 19(1), pp.112-120.
[2] Arifin, R. and Egbelu, P.J., (2000) Determination of vehicle requirements in automated guided vehicle systems: a statistical approach, Production Planning and Control, 11(3), pp. 258-270.
[3] Baker, B.M. and Ayechew, M.A., (2003) A generic algorithm for the vehicle routing problem, Computers and Operations Research, 30(5), pp.787-800.
[4] Balan, R.K., Khoa, N. X. and Jiang, L., (2011) Real-time trip information service for a large taxi fleet, Proceedings of the 9th international conference on Mobile Systems, pp.99-112.
[5] Baras, J.S. and Dorsey, A.J., (1981) Stochastic control of two partially observed competing queues, IEEE Transactions on Automatic Control, 26(5), pp.1106-17.
[6] Brain, M., Gould, R., Kaempf, U. and Wehrung, B. (1999) Emerging Needs for Continuous Flow FOUP Transport, Proceedings of the IEEE/CPMT International Electronics Manufacturing Technology (IEMT) Symposium, pp.76-82.
[7] Campbell, E., Wright, R., Cheatham, J., Schulz, M., and Berry, J. L., (2000) Simulation modeling for 300mm semiconductor factories, Solid State Technology, 43(10), pp. 95-104.
[8] Cardarelli, G. and Pelagagge, P. M., (1995) Simulation tool for design and management optimization of automated interbay material handling and storage systems for large wafer fab, IEEE Transactions on Semiconductor Manufacturing, 8(1), pp.44-49.
[9] Cardarelli, G., Pelagagge, P. M. and Granito, A., (1996) Performance analysis of automated interbay material-handling and storage systems for large wafer fab, Robotics and Computer-Integtated Manufacturing, 12(3), pp.227-234.
[10] Chen, L., Feng, Y., Hao, G. and Jang, J., (2015) Optimal pricing and sequencing in a Make-to-Order system with batch demand, IEEE Transactions on Automatic Control, 60(6), pp. 1455-1470.
[11] Chung, J. and Jang, J., (2007) The integrated room layout for a semiconductor facility plan, IEEE Transactions on Manufacturing Manufacturing, 20(4), pp. 517-527.
[12] Down, D.G. and Lewis, M.E., (2006) Dynamic load balancing in parallel queueing systems, Stability and Optimal Control, 168(2), pp.509-519.
[13] Egbelu, P.J. and Tanchoco, J.M.A., (1984) Characterization of automatic guided vehicle dispatching rules, International Journal of Production Research, 22(3), pp.359-374.
[14] Egbelu, P. J., (1987) Pull versus push strategy for automated guided vehicle load movement in a batch manufacturing system, Journal of Manufacturing System, 6(3), pp.271-280.
[15] Egbelu, P. J., (1987) The use of non-simulation approaches in estimating vehicle requirements in an automated guided vehicle based transport system, Material Flow, 4(1), pp.17-32.
[16] Grillo, S., Pievatolo, A. and Tironi, E., (2016) Optimal storage scheduling using Markov decision processes, IEEE Transactions on Sustainable Energy, 7(2), pp.755-764.
[17] Heung, T.H., Ho, T.K. and Fung, Y.F., (2005) Coordinated road-junction traffic control by dynamic programming, IEEE Transactions on Intelligent Transportation Systems, 6(3), pp.341-350.
[18] Huang, C. J., Chang, K.H. and Lin, J. T., (2012), Optimal vehicle allocation for an automated materials handling system using simulation optimization, International Journal of Production Research, 50(20), 5734-5746.
[19] Huang, C. W. and Lin, J. T., (2016), A pre-dispatching vehicle method for a diffusion area in a 300 mm wafer fab, Journal of Industrial and Production Engineering, (Accepted on March 27, 2016).
[20] Im, T.H., Ho, T.K. and Fung, Y.F., (2005) Coordinated road-junction traffic control by dynamic programming, IEEE Transactions on Intelligent Transportation Systems, 6(3), pp.341-350.
[21] Kim, S., Lewis, M.E., Chelsea, I. and White, C., (2005) Optimal vehicle routing with real-time traffic information, IEEE Transactions on Intelligent Transportation Systems, 6(2), pp.178-188.
[22] Kobza, K., Kim, K., Moon Y., Park, T. and Lee, S., (2010) The deadlock detection and resolution method for a unified transport system, International Journal of Production Research, 48(15), pp.4423-4435.
[23] Koo, P. H. and Jang J., (2002) Vehicle travel time models for AGV systems under various dispatching rules, International Journal of Flexible Manufacturing Systems, 14(3), pp. 249-261.
[24] Kurosaki, R., Nagao, N., Komada, H., Watanabe, Y. and Yano, H., (1997) AMHS for 300mm wafer, IEEE International Symposium on Semiconductor Manufacturing Conference, pp.13-16.
[25] Kyriakidis, E.G. and Pavitsos, A., (2009) Markov decision models for the optimal maintenance of a production unit with an upstream buffer, Computers and Operations Research, 36(6), pp.1993-2006.
[26] Le-Anh, T. and Koster, D., (2006) A review of design and control of automated guided vehicle systems, European Journal of Operational Research, 171(1), pp.1-23.
[27] Levitin, G. and Abezgaouz, R., (2003) Optimal routing of multiple-load AGV subject to LIFO loading constraints, Computers and Operations Research, 30(3), pp. 397-410.
[28] Li, Z. and Tao, F., (2010) On determining optimal fleet size and vehicle transfer policy for a car rental company, Computers and Operations Research, 37(2), pp.341-350.
[29] Liao, D.Y. and Fu, H.S., (2004) Speed delivery: dynamic OHT allocation and dispatching in large-scale 300-mm AMHS management, IEEE Robotics and Automation Magazine, 11(3), pp.22-32.
[30] Liao, D. Y., Jeng M. D. and Zhou, M. C., (2007) Application of Petri net and largrangian relaxation to scheduling automatic material-handling vehicles in 300-mm semiconductor manufacturing, IEEE Transactions on Systems, Man, and Cybernetics, 37(4), pp. 504-516.
[31] Lin, J. T., Wang, F. K. and Chang, Y. M., (2006) A hybrid push/pull-dispatching rule for a photobay in a 300mm wafer fab, Robotics and Computer-Integrated Manufacturing, 22(1), pp. 47-55.
[32] Lin, J.T., Wang, F.K. and Wu, C.K., (2003) Connecting transport AMHS in a wafer fab, International Journal of Production Research, 41(3), pp.529-544.
[33] Lin, J.T, Wang, F.K. and Wu, C.K., (2003) Simulation analysis of the connecting transport AMHS in a wafer fab, IEEE Transactions on Semiconductor Manufacturing, 16(3), pp.555-564.
[34] Lin, J. T., Wang, F. K. and Yen, P. Y., (2001) Simulation analysis of dispatching rules for an automated interbay material handling system in wafer fab, International Journal Production Research, 39(6), pp.1221-1238.
[35] Lin, J. T., Wang F. K. and Yen, P. Y., (2004) The maximum loading and the optimum number of vehicles in a double-loop of an interbay material handling system, Production Planning & Control, 15(3), pp. 247-255.
[36] Lin, J. T., Wu, C. H. and Huang, C. W., (2013) Dynamic vehicle allocation control for automated material handling system in semiconductor manufacturing, Computers & Operations Research, 40(10), pp.2329-2339.
[37] Lippman, S.A., (1975) Applying a new device in the optimization of exponential queuing systems, Operations Research, 23(4), pp.687-710.
[38] Mackulak, G. T., Lawrence, F. P. and Rayter, J., (1998) Simulation analysis of 300mm intrabay automation vehicle capacity alternatives, Advanced Semiconductor Manufacturing Conference and Workshop, pp.445-450.
[39] Mackulak, G. T. and Savory, P., (2001) A simulation-based experiment for comparing amhs performance in a semiconductor fabrication facility, IEEE Transaction Semiconductor Manufacturing, 14(3), pp.273-280.
[40] Mahadevan, B. and Narendran, T. T., (1990) Design of an automated guided vehicle based material handling system for a flexible manufacturing system, International Journal of Production Research, 28(9), pp.1611-1622.
[41] Mahadevan, B. and Narendran, T. T., (1993) Estimation of number of AGVs for an FMS: an analytical model, International Journal of Production Research, 31(7), pp.1655-1670.
[42] Maxwell, W.L. and Muckstadt, J.A., (1982) Design of automatic guided vehicle systems. IIE Transaction, 14(2), pp.114-124.
[43] Min, H. and Yih, Y., (2003) Selection of dispatching rules on multiple dispatching decision points in real-time scheduling of a semiconductor wafer fabrication system, International Journal of Production Research, 41(16), pp.3921-3941.
[44] Monch, L., Fowler, J., Dauzere-Peres, S., Mason, S. and Rose O., (2011) A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations, Journal of Scheduling, 14(6), pp.583-599.
[45] Nadoli, G. and Pillai, D., (1994) Simulation in automated material handling system design for semiconductor manufacturing, Winter Simulation Conference, pp. 892-899.
[46] Nazzal, D. and Bodner, D.A., (2003) A simulation-based design framework for automated material handling systems in 300mm fabrication facilities, Winter Simulation Conference, pp.1351-1359.
[47] Negahban, A. and Smith, J.S., (2014) Simulation for manufacturing system design and operation: Literature review and analysis, Journal of Manufacturing Systems, 33(2), pp.241-261.
[48] Peters, B. A. and Yang, T., (1997) Integrated facility layout and material handling system design in semiconductor fabrication facilities, IEEE Transactions on Semiconductor Manufacturing, 10(3), pp.360-369.
[49] Pierce, N. G. and Stafford, R., (1994) Modeling and simulation of material handling for semiconductor wafer fabrication, Winter Simulation Conference, pp.900-906.
[50] Pillai, D., Quinn, T., Kryder, K. and Charlson, D., (1999) Integration of 300mm fab layouts and material handling automation, IEEE International Symposium on Semiconductor Manufacturing, pp. 23-26.
[51] Puterman, M., (1994) Markov decision process: discrete stochastic dynamic programming, John Wiley & Sons, Inc. New York.
[52] Qin, W., Zhang, J. and Sun, Y., (2013) Multiple-objective scheduling for interbay AMHS by using genetic-programming-based composite dispatching rules generator, Computers in Industry, 64(6), pp. 694-707.
[53] Renaud, J., Laporte, G. and Boctor, F., (1996) A tabu search heuristic for the multi-depot vehicle routing problem, Computers and Operations Research, 23(3), pp.229-235.
[54] Rothe, J., Gaxiola, G., Marshall, L., Asakawa, T., Yamagata, K. and Yamamoto, M., (2015) Novel approaches to optimizing carrier logistics in semiconductor manufacturing, IEEE Transactions on Semiconductor Manufacturing, 28(4), pp.494-501.
[55] Sennott, L.I., (1998) Stochastic dynamic programming and the control of queueing systems, John Wiley & Sons, Inc. New York.
[56] Seow, K. T., Dang, N. H. and Lee, D. H. (2010) A collaborative multiagent taxi-dispatch system, IEEE Transactions on Automation Science and Engineering, 7(3), pp.607-616.
[57] Sha, D. Y., Lin, J. T. and Yang, C. J. (2008) The evaluation of search range assignment in 300mm automated material handling system (AMHS), International Journal of Advanced Manufacturing Technology, 35(7), pp.697-710.
[58] Stubbe, K. and Rose, O., (2011), Simulation analysis of semiconductor manufacturing Simulation analysis of semiconductor manufacturing with small lot size and batch tool replacements, European Journal of Industrial Engineering, 5(3), pp. 292-312.
[59] Tanchoco, J. M. A., Egbelu, P. J. and Taghaboni, F., (1987), Determination of the total number of vehicles in an AGV-based material transport system, Material Flow, 4(1), pp. 33-51.
[60] Ting, J. H. and Tanchoco, J. M. A., (2001) Optimal bi-directional spine layout for overhead material handling systems, IEEE Transactions on Semiconductor Manufacturing, 14(1), pp.57-64.
[61] Tung, J., Sheen, T., Kao M. and Chen, C. H., (2013) Optimization of AMHS design for a semiconductor foundry fab by using simulation modeling, Winter Simulation Conference, pp. 3829-3839.
[62] Wang, F.K. and Lin, J.T., (2004) Performance evaluation of an automated material handling system for a wafer fab, Robotics and Computer Integrated Manufacturing, 20(2), pp.91-100.
[63] Wong, M. M., Tan, C. H., Zhang, J. B., Zhuang, L. Q., Zhao Y. Z. and Luo, M., (2007) On-line reconfiguration to enhance the routing flexibility of complex automated material handling operations, Robotics and Computer-Integrated Manufacturing, 23(3), pp. 294-304.
[64] Wu, C. H., Lin, J. T. and Chien, W. C., (2010) Dynamic production control in a serial line with process queue time constraint, International Journal of Production Research, 48(13), pp. 3823-3843.
[65] Wu, C. H., Lin, J. T. and Chien, W. C., (2012) Dynamic production control in parallel processing systems under process queue time constraints, Computers & Industrial Engineering, 63(1), pp. 192-203.
[66] Yang, T. and Peters, B. A., (1997) A spine layout design method for semiconductor fabrication facilities containing automated material-handling systems, International Journal Operations Production Management, 17(5), pp. 490-501.
[67] Yang, T., Rajasekharan, M. and Peters, B. A., (1999) Semiconductor fabrication facility design using a hybrid search methodology, Commuters and Industrial Engineering, 36(3), pp.565-583.
[68] Zimmerhackl, O., Rothe, J., Schmidt, K., Marshall L. and Honold, A., (2007) The effects of small lot manufacturing on AMHS operation and equipment front-end design, International Symposium on Semiconductor Manufacturing, 36(3), pp.565-583.