Abstract
The problem of maximizing the throughput of Semiconductor Wafer Fabrication Systems is addressed. We model the fabrication systems as a Stochastic Timed Automata and design a discrete-event simulation scheme. The simulation scheme is explicit, fast and achieves high fidelity which captures the feature of reentrant process flow and is flexible to accommodate diversified wafer lot scheduling policies. A series of Marginal Machine Allocation Algorithms are proposed to sequentially allocate machines. Numerical experiments suggest the designed methods are efficient to find good allocation solutions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
References
Brown S M, Hanschke T, Meents I, Wheeler B R, Zisgen H (2010). Queueing model improves IBM’s semiconductor capacity and lead-time management. INFORMS Journal on Applied Analytics 40(5): 397–407.
Burton G (2017). TSMC says 3nm plant could cost it more than $20bn. https://web.archive.org/web/20171012043608/https://www.theinquirer.net/inquirer/news/3018890/tsmc-says-3nm-plant-could-cost-it-more-than-usd20bn, accessed on May 23, 2022.
Cassandras C G, Lafortune S (2008). Introduction to Discrete Event Systems(2ed). Springer, New York.
Çatay B, Erengüç Ş S, Vakharia A J (2003). Tool capacity planning in semiconductor manufacturing. Computers & Operations Research 30(9): 1349–1366.
Chen T (2012). Intelligent scheduling approaches for a wafer fabrication factory. Journal of Intelligent Manufacturing 23(3): 897–911.
Cigolini R, Franceschetto S, Sianesi A (2022). Shop floor control in the VLSI circuit manufacturing: A simulation approach and a case study. International Journal of Production Research 60(18): 5450–5467.
Connors D P, Feigin G E, Yao D D (1996). A queueing network model for semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing 9(3): 412–427.
Crist K, Uzsoy R (2011). Prioritising production and engineering lots in wafer fabrication facilities: A simulation study. International Journal of Production Research 49(11): 3105–3125.
Fowler J W, Mönch L, Ponsignon T (2015). Discrete-event simulation for semiconductor wafer fabrication facilities: A tutorial. International Journal of Industrial Engineering 22(5): 661–682.
Geng N, Jiang Z (2009). A review on strategic capacity planning for the semiconductor manufacturing industry. International Journal of Production Research 47(13): 3639–3655.
Geng N, Jiang Z, Chen F (2009). Stochastic programming based capacity planning for semiconductor wafer fab with uncertain demand and capacity. European Journal of Operational Research 198(3): 899–908.
Ghasemi A, Azzouz R, Laipple G, Kabak, K E, Heavey C (2020). Optimizing capacity allocation in semiconductor manufacturing photolithography area—case study: Robert bosch. Journal of Manufacturing Systems 54: 123–137.
Goodwin T, Xu J, Celik N, Chen C H (2022). Realtime digital twin-based optimization with predictive simulation learning. Journal of Simulation. DOI: https://doi.org/10.1080/17477778.2022.2046520.
Hsieh B W, Chen C H, Chang S C (2007). Efficient simulation-based composition of scheduling policies by integrating ordinal optimization with design of experiment. IEEE Transactions on Automation Science and Engineering 4(4): 553–568.
Hsieh L Y, Chang K H, Chien C F (2014). Efficient development of cycle time response surfaces using progressive simulation metamodeling. International Journal of Production Research 52(10): 3097–3109.
Kopp D, Hassoun M, Kalir A, Mönch L (2020). SMT2020 — A semiconductor manufacturing testbed. IEEE Transactions on Semiconductor Manufacturing 33(4): 522–531.
Kumar P, Meyn S P (1995). Stability of queueing networks and scheduling policies. IEEE Transactions on Automatic Control 40(2): 251–260.
Kumar S, Kumar P (2001). Queueing network models in the design and analysis of semiconductor wafer fabs. IEEE Transactions on Robotics and Automation 17(5): 548–561.
Liu M (2005). The advanced foundry in the consumer electronics era. Keynote Presentation at 2nd ISMI Symposium on Manufacturing Effectiveness, USA.
Lu S C, Ramaswamy D, Kumar P (1994). Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants. IEEE Transactions on Semiconductor Manufacturing 7(3): 374–388.
Morgan J (2022). Supply chain issues and autos: When will the chip shortage end? https://www.jpmorgan.com/insights/research/supply-chain-chip-shortage, accessed on Jan 02, 2023.
Peng Y, Xu J, Lee L H, Hu J, Chen C H (2018). Efficient simulation sampling allocation using multifidelity models. IEEE Transactions on Automatic Control 64(8): 3156–3169.
Perkins J R, Humes C, Kumar P (1994). Distributed scheduling of flexible manufacturing systems: Stability and performance. IEEE Transactions on Robotics and Automation 10(2): 133–141.
Shanthikumar J G, Yao D D (1988). On server allocation in multiple center manufacturing systems. Operations Research 36(2): 333–342.
Weber R R (1980). Note — On the marginal benefit of adding servers to g/gi/m queues. Management Science 26(9): 946–951.
Wu Y (2023). A cpp implementation of SWFS simulation. https://github.com/xmlongan/SWFS.git, accessed on Jan 4, 2023.
Wu Y, Chong I G (2017). Machine allocation in a semiconductor wafer fabrication system. 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference, China.
Yang F, Ankenman B, Nelson B L (2007). Efficient generation of cycle time-throughput curves through simulation and metamodeling. Naval Research Logistics 54(1): 78–93.
Yang F, Ankenman B E, Nelson B L (2008). Estimating cycle time percentile curves for manufacturing systems via simulation. INFORMS Journal on Computing 20(4): 628–643.
Yeong-Dae K, Dong-Ho L, Jung-Ug K, Hwan-Kyun R (1998). A simulation study on lot release control, mask scheduling, and batch scheduling in semiconductor wafer fabrication facilities. Journal of Manufacturing Systems 17(2): 107–117.
Zhang F, Song J, Dai Y, Xu J (2020). Semiconductor wafer fabrication production planning using multi-fidelity simulation optimisation. International Journal of Production Research 58(21): 6585–6600.
Zhang Z, Guan Z, Gong Y, Shen Q (2021). Multi-fidelity simulation-based optimisation for large-scale production release planning in wafer fabs. IFIP International Conference on Advances in Production Management Systems, France.
Zhang Z, Guan Z, Gong Y, Luo D, Yue L (2022). Improved multi-fidelity simulation-based optimisation: Application in a digital twin shop floor. International Journal of Production Research 60(3): 1016–1035.
Acknowledgments
This work is supported in partial by the National Natural Science Foundation of China (NSFC) under Grant No. U2268209. The authors thank the editor and three anonymous reviewers for their comments and suggestions which help to improve the article greatly.
Author information
Authors and Affiliations
Corresponding author
Additional information
Yanfeng Wu is an assistant professor at the School of Finance, Jiangxi University of Finance and Economics. He received his Ph.D. from Fudan University. His research interests include discrete-event stochastic systems, stochastic optimization and statistical inference.
Sihua Chen is a professor at the School of Information Management, Jiangxi University of Finance and Economics. His research interests include human-computer intersection, hybrid intelligence, e-commerce, business intelligence, big data analysis and application.
Rights and permissions
About this article
Cite this article
Wu, Y., Chen, S. Machine Allocation in Semiconductor Wafer Fabrication Systems: A Simulation-Based Approach. J. Syst. Sci. Syst. Eng. 32, 372–390 (2023). https://doi.org/10.1007/s11518-023-5558-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11518-023-5558-8