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研究生： 陳金鳳
Chen, Chin-Feng
論文名稱： 多產品多機台半導體製造程序之最佳派遣策略及系統模擬
Optimal Dispatching Policy and Simulation Studies for Multi-Product Multi-Tool Semiconductor Manufacturing Processes
指導教授： 張珏庭
Chang, Chuei-Tin
學位類別： 碩士
Master
系所名稱： 工學院 - 化學工程學系
Department of Chemical Engineering
論文出版年： 2009
畢業學年度： 97
語文別： 英文
論文頁數： 156
中文關鍵詞： 數值模擬 、EWMA 、派遣策略 、排隊理論 、半導體製造
外文關鍵詞： semiconductor manufacturing, dispatching policy, queuing theory, EWMA, numerical simulation
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    • 半導體製造是一個快速成長的工業，由於元件尺寸不斷縮小及晶圓尺吋不斷增大，因此如何利用精密且複雜控制方法來改善產品品質及機台利用率將顯得格外重要。在本研究中，我們將半導體製造程序視為多個平行的 排隊系統，並假設以EWMA控制器來逐批調整製程輸入。根據這些假設，在本研究中我們提出一個混合整數非線性規劃模式來決定最佳派遣策略，可以將產品品質指標最大化或機台利用率最小化，另外也發展出系統化的數值模擬方法來驗證派遣模式之合理性。此外，我們也在模擬研究中探討了不同參數值對產品品質指標的影響，並找出其最佳值。最後，由於實際上並不一定能得到模式中正確的參數估計值，我們也建議了可允許的參數範圍，可用來獲得可接受的產品品質指標。

    Semiconductor manufacturing is one of the most fast-growing industries in today’s world. As feature sizes shrink and wafer sizes increase, intricate control methods are needed to improve the product quality and tools utilization. In this thesis, the semiconductor manufacturing process is treated as multiple queuing systems operated in parallel and, also, it is assumed that the exponentially weighed moving average (EWMA) controller is implemented to adjust the process recipe of each system from run to run. Based on these assumptions, a mixed integer nonlinear programming model is formulated to determine the optimal dispatching policies for maximizing process capability or minimizing tool utilization rate. Systematic numerical simulation procedure is also devised to confirm the validity of the dispatching model. The simulation results show that the predictions of this model are reasonable. Moreover, the impacts of changing parameters values are investigated in extensive case studies and their optimal values are identified also. Finally, since accurate estimates of the model parameters may not always be available, the allowable range of tuning parameter is recommended to achieve an acceptable process capability.

    1 Introduction…………………………………………………………1 2 Semiconductor Process Control………………………………… 4 2.1 Time Series…………………………………………………… 4 2.1.1　Linear filter model…………………………………4 2.1.2　Autoregressive models………………………………7 2.1.3　Moving average models………………………………8 2.1.4　Mixed autoregressive-moving average models… 9 2.1.5　Non-stationary models………………………………9 2.1.6　Integrated moving average processes………… 12 2.2 Run-by-Run Control………………………………………… 15 2.2.1　Single-Variable Control Strategy………………17 2.2.2　Gradual Drift……………………………………… 18 2.3 Characterization of Product Quality……………………21 2.4Simulation Studies……………………………………………29 3 Queueing Theory……………………………………………………33 3.1 Queueing Theory………………………………………………33 3.2 The Queueing System…………………………………………49 3.3 Simulation Procedure……………………………………… 54 4 Optimal Dispatching Policy for the Multi-Product Multi- Tool Processes…………………………………………………… 58 4.1 Optimal Dispatching Policy……………………………… 58 4.2 Mathematical Programming Model………………………… 60 4.3 Simple Example……………………………………………… 65 4.3.1　Optimal Dispatching Policy Obtained by Minimizing Utilization Rate…………………… 67 4.3.2　Optimal Dispatching Policy Obtained by Maximizing Process Capability………………… 70 5 Simulation Procedures of Multi-Product Multi-Tool Processes……………………………………………………………73 5.1 Simulation Strategy for a Multi-Product Queueing System………………………………………………………… 73 5.2 Simulation Strategy for a Multi-Product RbR Control System………………………………………………………… 77 5.3 Simulation Studies of a Multi-Product Multi-Tool Process…………………………………………………………79 5.3.1　Simulation Studies: Minimizing the Total Utilization Rate……………………………………81 5.3.2　Simulation Studies: Maximizing the Process Capability……………………………………………91 5.3.3　Simulation Studies: Random Dispatch…………101 6 Case Studies………………………………………………………111 6.1 Impacts of Time Correlation in IMA(1,1) Process… 111 6.2 Impacts of EWMA Controller Tuning Parameters………119 6.3 Impacts of Mismatch Parameters…………………………127 6.3.1　Inaccurate Time Correlation Coefficient……129 6.3.2　Several Mismatched Model Parameters…………133 7 Conclusions and Future Works…………………………………137 References……………………………………………………………139 Appendix A：Simulation Studies…………………………………143 Appendix B：Maximizing Process Capability………………… 145 Appendix C：Simulation Procedure………………………………149

    Bhaskaran, K. & Pinedo, M. In Handbook of Industrial Engineering, edited by G. Salvendy. 1992 (John Wiley: New York, NY).
    Blackstone, J. H., Phillips, D. T. & Hogg, G. L. A state-of-the-art survey of dispatching rules for manufacturing job shop operations. Int. J. Prod. Res., 1982, 20, 27–45.
    Box, G. E. P., Jenkins, G. M. & Reinsel, G. Time Series Analysis Forecasting And Control(3rd Ed.). Prentice-Hall, 1994.
    Cassandras, C. G. & Lafortune, S. Introduction To Discrete Event System. Kluwer Academic. 1999.
    Choi J. Y. & Reveliotis, S. Relative value function approximation for the capacitated re-entrant line scheduling problem. IEEE Trans. Autom. Sci. Eng., vol. 2, no. 3, pp. 285–299, Jul. 2005.
    Dabbas, R. M., Chen, H. N. & Fowler J. W. et al., A combined dispatching criteria approach to scheduling semiconductor manufacturing systems. Comput. Ind. Eng., vol. 39, no. 3–4, pp. 307–324, Apr. 2001.
    Dabbas, R. M. & Fowler, J. W. A new scheduling approach using combined dispatching criteria in wafer fabs. IEEE Trans. Semiconduct. Manufact., vol. 16, no. 3, pp. 501–510, Aug. 2003.
    Del Castillo, E., Statistical Process Adjustment for Quality Control. John-Wiley & Sons. New York, 2002.
    Firth, S. K., Campbell, W. J., Toprac, A. & Edgar, T. F. Just-in-time adaptive disturbance estimation for run-to-run control of semiconductor processes. IEEE Trans. Semicond. Manuf. 19 (2006) 298–315.
    Kutanoglu, E. & Sabuncuoglu, I. An analysis of heuristics in a dynamic job shop with weighted tardiness objectives. Int. J. Prod. Res., 1999, 37, 165–187.
    Lee, R. Uzsoy, C. & Martin-Vega, L. A review of production planning and scheduling models in the semiconductor industry, part II: Shop floor control. IIE Trans. Scheduling Logistics, vol. 26, no. 5, pp. 44–55, Sept. 1994.
    Lee, Y. H. & Kim, T. Manufacturing cycle time reduction using balance control in the semiconductor fabrication line. Production Planning Control, vol. 13, no. 6, pp. 529–540, Sept. 2002.
    Ma, M. D., Chang, C. C., Wong, D. S. H.& Jang, S. S. Identification of tool and product effects in a mixed product and parallel tool environment. Journal of Process Control. 2008.
    May, G. S. & Spanos, C. J. Fundamentals Of Semiconductor Manufacturing And Process Control. John Wiley & Sons. 2006.
    Mittler, M. & Schoemig, A. K. Comparison of dispatching rules for semiconductor manufacturing using large facility model. in Proc. 1999 Winter Simulation Conf., Phoenix, AZ, 1999, pp. 709–713.
    Morrison, J., Janakiram, M. & Kumar, P. R. A comparative study of scheduling policies at Motorola fabs, in Proceedings of the International Conference on Semiconductor Manufacturing Operational Modeling and Simulation. San Francisco, 1999, pp. 51–56.
    Moyne, J. Run-to-Run Control in Semiconductor Manufacturing. CRC Press, Florida, 2001.
    Olkin, Ingram., Gleser, Leon J. & Derman, Cyrus., Probability Models And Applications. New York, 1980.
    Pasadyn, A. J. & Edgar, T. F., Observability and state estimation for multiple product control in semiconductor manufacturing. IEEE Trans. Semicond. Manuf. 18 (2005) 592–604.
    Patel, N. S. & Jenkins, S. T. Adaptive optimization of run-to-run controllers: the EWMA example. IEEE Trans. Semicond. Manuf., vol. 13, pp. 97-107, 2000.
    Pierce, N. G. & Yurtsever, T. Dynamic dispatch and graphical monitoring system, in Proceedings of the International Conference on Semiconductor Manufacturing Operational Modeling and Simulation, San Francisco. 1999, pp. 57–61.
    Qu, P. & Mason, S. J. Metaheuristic scheduling of 300-mm lots containing multiple orders. IEEE Trans. Semiconduct. Manufact., vol. 18, no. 4, pp. 633–643, Nov. 2005.
    Raghu, T. S. & Rajendran, C. An efficient dynamic dispatching rule for scheduling in a job shop. Int. J. Prod. Econ., 1993, 32, 301–313.
    Rajendran, C. & Holthaus, O. A comparative study of dispatching rules in dynamic flowshops and jobshops. Eur. J. Op. Res., 1999, 116, 156–170.
    Sachs, E., Hu, A. & Ingolfsson, A. Run by run process control: combining SPC and feedback control, IEEE Trans. Semicont. Manuf., vol. 8, pp. 26-43, 1995.
    Smith, T. H. & Boning, D. S. Artificial neural network exponentially weighted moving average controller for semiconductor processes, J. Vacuum Science Tech., vol. 15, pp. 236-239, 1997.
    Tseng, S. T., Yeh, A. B., Tsung, F. & Chan, Y. Y. A study of variable EWMA controller. IEEE Trans. Semicond. Manuf., vol. 16, pp. 633-643, 2003.
    Wang, Zuntong., Wu, Qidi. & Qiao, Fei. A Lot Dispatching Strategy Integrating WIP Management and Wafer Start Control. IEEE Trans. Autom. Sci. Eng., vol. 4, no. 4, pp. 579–583, Jul. 2007.
    Wein, L. M. Scheduling semiconductor wafer fabrication. IEEE Trans. on Semiconductor Manufacturing. vol. 1, no. 3, pp. 115–130, Aug. 1988.
    Wu, M. F., Lin, C. H., Wong, D. S. H., Jang, S. S. & Tseng, S. S. Performance Analysis of EWMA Controllers Subject to Metrology Delay. IEEE Trans. on Semiconductor Manufacturing. vol. 21, no. 3, pp. 413–425, Aug. 2008.
    Wu, M. F., Lin, W. K., Ho, C. L., Wong, D. S. H., Jang, S. S., Zheng, Y. & Jain, A. A Feed-Forward/Feedback Run-to-Run Control of a Mixed Product Process: Simulation and Experimental Studies. Ind. Eng. Chem. Res. 2007, 46, 6963-6970.
    Zheng, Y., Lin, Q. H., Wong, D. S. H., Jang, S. S. & Hui, K. Stability and performance analysis of mixed product run-to-run control. J. Process. Control 16 (2006) 431–443.

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