晶圓廠自動化物料搬運系統之搬運策略模擬研究

Simulation Analysis of Transport Strategies for Automated Material Handling System in Wafer Fab

楊景如(Ching-Ju Yang)

指導教授 ： 沙永傑 ； 洪瑞雲

國立交通大學/管理學院/工業工程與管理系所/博士(2009年)

https://doi.org/10.6842/NCTU.2009.01192

摘要

在300mm晶圓廠搬運系統架構中，搬運車不僅限駛於單一製程中心，而可行駛於整廠。如此晶圓批(FOUP)需至下一製程機台加工時，可經由倉儲系統轉運至目的機台，或以機台對機台(tool-to-tool)的方式直接運送。搬運策略的發展在這新穎的搬運設施下顯的重要。本論文提出兩項搬運策略議題，並以國內某大晶圓廠為研究對象，利用系統模擬模式評估搬運策略績效。期望藉由合適搬運策略之發展，發揮該設施賦予彈性傳輸功能之效益。
第一項搬運策略，為派車時之搜尋範圍(Search Range，SR)指派議題。搜尋範圍之指派，為決定並限定某距離內之待搬運晶圓批(Waiting FOUP，WF)或閒置搬運車(Idle Vehicle，IV)，可考量被搬運或執行搬運命令，進而間接限制搬運車空車行進距離，使搬運資源有效利用。一個兩階段方法(two-phase approach)被提出。由模擬模式中之空車行進距離歷史記錄可得知，當派車被執行當下，系統中的待搬運晶圓批(WF)數或閒置搬運車(IV)數，會影響搬運車空車行進的鉅離；且當待搬運晶圓批數或閒置搬運車數越少時，空車行進距離越長。因此階段一為利用空車行進距離之歷史記錄，來訂定搜尋範圍之多個水準。階段二為，對階段一訂定之搜尋範圍水準進行評估。該多水準設定之精神，為派車時，根據不同待搬運晶圓批數或閒置搬運車數之系統況態下，給定不同的搜尋範圍。於本研究案例之實驗結果顯示，搜尋範圍的設定，顯著影響搬運績效，且較短搜尋範圍之設定，適用於搬運負荷較重之系統；搬運負荷較輕之系統，則適用較長之搜尋範圍。
第二項搬運策略，為因應全自動化製造之搬運模式，發展出之機台派工與搬運派車之整合指派(Integrated Dispatching，ID)架構。在該架構下，排除生產障礙及避免產能損失之三項搬運策略：避免壅塞(avoid blocking)、避免飢餓(avoid starvation)、加速集批準備(accelerate batch preparation)被被提出，輔以模擬評估於整合指派(ID)架構中。該整合架構涵蓋五階段決策程序，包括派工/派車要求、資源狀態確認、候選指派選擇、派工/派車法則、派工/派車執行。其中第三階段決策程序之候選指派選擇，包含五類選擇：晶圓批選擇機台(FST)、晶圓批選擇倉儲(FSS)、機台選擇晶圓批(TSF)、晶圓批選擇搬運車(FSV)、搬運車選擇晶圓批(VSF)。而所提出之三項搬運策略，被執行並評估於搬運車選擇晶圓批(VSF)中。於本研究案例之實驗結果顯示，所提出之三項搬運策略顯著影響系統績效，並使得績效指標有較佳表現。

關鍵字

搬運策略 ； 派車 ； 整合 ； 自動化物料搬運系統 ； 模擬

並列摘要

In the 300 mm wafer fab with connected loops track design, the vehicle can travel not just in one process center but all around the wide fab, and FOUP can be delivered either through stocker or tool-to-tool directly. Transport strategy development becomes important in this novel facility. In this dissertation, two issues of transport strategies were explored, and the simulation models abstracted from two wafer fabs in Taiwan were used to evaluate the transport strategies and attempt to bring this flexible transport configuration to a beneficial result.
The first issue, Search Range (SR) assignment, is to determine how far the waiting FOUPs (WFs) or idle vehicles (IVs) should be considered for transport task when dispatching occurs, and then indirectly limit the distance of vehicle’s empty trip (DVemp) to make the vehicle work effectively. A two-phase approach with simulation has been developed to assign the Search Range (SR) for studying this idea. In phase I, the number of WF and IV in the system at the time of dispatching will affect DVemp. Further, the SR was assigned and evaluated based on the average and standard deviation of DVemp under different numbers of WF and IV in phase II. The results indicated that the SR significantly affects the performance, and a longer SR used in a light system is feasible; a shorter SR is applicable for a heavy system.
Second, the transport strategies named as Integrated Dispatching (ID) in Tool and Vehicle Dispatching Integrated (TVDI) architecture in a fully-automated manufacturing wafer fab were addressed. At present, there are three transport strategies involved in vehicle dispatching, namely, avoid blocking, avoid starvation, and accelerate batch preparation. These strategies were developed to obviate production obstacles and to avoid capacity loss. Consequently, there are five levels in the decision-making process of TVDI, namely, dispatching request, conditions checking, candidate selection, dispatching rules, and result execution. Specifically, candidate selection was classified into five categories: FOUP-selects-tool (FST), FOUP-selects-stocker (FSS), tool-selects-FOUP (TSF), FOUP-selects-vehicle (FSV), and vehicle-selects-FOUP (VSF). The proposed transport strategies were further implemented in VSF. The simulation results show that the differences in the proposed strategies compared with ignoring the issues are statistically significant, and the performances of the wafer output, cycle time, and waiting time can be improved.

並列關鍵字

Transport strategy ； Dispatching ； Integrated ； AMHS ； Simulation

參考文獻

[1] Akcalt E., Nemoto K. and Uzsoy R. (2001) Cycle-Time Improvements for Photolithography Process in Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing, 14(1), 48-56.

[2] Arifin R. and Egbelu P. J. (2000) Determination of vehicle requirements in automated guided vehicle systems: a statistical approach. Production Planning & Control, 11(3) 258-270.

[3] Bahri N., Reiss J. and Doherty B. (2001) A comparison of unified vs. segregated automated material handling systems for 300 mm fabs. Proceedings of the International Symposium on Semiconductor Manufacturing Conference, 3-6.

[4] Bartholdi J.J. and Platzman L.K. (1989) Decentralised control of automated guided vehicles on a simple loop. IIE Transactions, 21(1), 76–81.

[5] Binder H. and Honold A. (1999) Automation and fab concepts for 300 mm wafer manufacturing. Microelectronic Engineering, 45(2/3), 91-100.