Abstract
Semiconductor wafer fabrication system is a typical complex manufacturing system, since it has large-scale, reentrant, multi-objective, uncertain and other characteristics. It’s too difficult to achieve the capacity balance to lead the existence of the bottleneck. According to the theory of TOC, the accurate detection of bottleneck is the key to implement DBR thought. For the characteristics of semiconductor production line, this paper proposes a bottleneck detection method based on the starvation and blockage information of the production line. The method is verified on HP-24 model by simulation. Compared to the relative load method, the equipment utilization law and the queue length method; the experimental results show that this method makes performance better than them.
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Cao Z, Peng Y, Wu Q (2010) DBR-based scheduling for re-entrant manufacturing system (in Chinese). In: 2010 Proceedings of contemporary integrated manufacturing system, vol 2010, pp 566–572
Ding X, Qiao F, Li L (2008) Research of DBR scheduling method for semiconductor manufacturing (in Chinese). Integr Mech Electr 2008:29–31
Kasemset C (2009) TOC based Procedure for Job-shop Scheduling. Doctoral Dissertation, Industrial Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, Bangkok, Thailand
Kasemset C, Kachitvichyanukul V (2009) Simulation tool for TOC implementation. In: Proceedings of ASIMMOD 2009, ASIMMOD 2009, Bangkok, Thailand, pp 86–97
Kasemset C, Kachitvichyanukuf V (2010) Effect of confidence interval on bottleneck identification via simulation. In: Proceedings of the 2010 IEEE IEEM. IEEE, DC, USA, pp 1592–1595
Li L, Chang Q, Ni J (2007) Bottleneck detection of manufacturing systems using data driven method. In: Proceedings of IEEE international conference on symposium on assembly and manufacturing. IEEE, Washington, DC, USA, pp 76–81
Li L, Chang Q, Ni J (2009) Data-driven bottleneck detection of manufacturing systems. Int J Prod Res 47(18):5019–5036
Murphy RE Jr, Dedera CR (1996) Holistic toc for maximum profitability. In: 1996 IEEE/SEMI advanced semiconductor manufacturing conference
Rahman S (1998) Theory of constraints: a review of the philosophy and its applications. Int J Oper Prod Manag 18(4):336–355
Roser C, Nakano M, Tanaka M (2002) Shifting bottleneck detection. In: Proceedings of the 34th conference on winter simulation. IEEE, Washington, DC, USA, pp 1079–1086
Roser C, Nakano M, Tanaka M (2003) Comparison of bottleneck detection methods for AGV systems. In: Proceedings of the 2003 winter simulation conference. IEEE, Washington, DC, USA, pp 1192–1198
Sengupta S, Das K, VanTil RP (2008) A new method for bottleneck detection. In: Proceedings of the 2008 winter simulation conference. IEEE, pp 1741–1745
Wang Z, Chen J, Wu Q (2008) A new method of dynamic bottleneck detection for semiconductor manufacturing line. In: Proceedings of the 17th world congress the international federation of automatic control, vol 17(1). Elsevier, Seoul, Korea, pp 14840–14845
Wu Q, Qiao F, Li L (2006) Semiconductor manufacturing system scheduling. Publishing House of Electronics Industry, Beijing
Zhai Y, Sun S, Wang J, Wang M (2010) Bottleneck detection method based on orthogonal experiment for job shop (in Chinese). Comput Integr Manuf Syst 16(9):1945–1952
Zhang R, Wu C (2012) Bottleneck machine identification method based on constraint transformation for job shop scheduling with genetic algorithm. Inf Sci 188:236–252
Zhou Z, Rose O (2009) A bottleneck detection and dynamic dispatching strategy for semiconductor wafer fabrication facilities. In: Proceedings of the 2009 winter simulation conference. Institute of Electrical and Electronics EngineersInc, Austin, TX, USA, pp 1646–1656
Acknowledgments
This research was supported by Chinese National Natural Science Foundation (61034004), Science and Technology Commission of Shanghai (10DZ1120100, 11ZR1440400), Program for New Century Excellent Talents in University (NCET-07-0622) and Shanghai Leading Academic Discipline Project (B004).
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Yu, Xy., Qiao, F., Ma, Ym. (2013). Bottleneck Detection Method Based on Production Line Information for Semiconductor Manufacturing System. In: Qi, E., Shen, J., Dou, R. (eds) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38391-5_22
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DOI: https://doi.org/10.1007/978-3-642-38391-5_22
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