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Storage prioritization by redistributing wafer lot transfers to enhance real-world fab throughput

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Abstract

Although efforts to improve the productivity of semiconductor fabs have mostly focused on processing machine scheduling, recent productivity drops due to insufficient automated material handling system (AMHS) resources have made the efficient control of AMHS a major issue in improving overall productivity. This study introduces a storage prioritization procedure (SPP) for the effective allocation of work-in-process (WIP) to storage devices is applied to a real-world 300 mm fab. The proposed SPP utilizes a minimum-cost flow-based model to generate priority lists of storage devices for wafer lot transfers after determining the push or pull strategy for each machine group. Experimental studies are conducted according to four simulation scenarios that demonstrate the superior performance of the SPP. The field application results verify the SPP performance in the real-world fab. The productivity improvement due to the SPP is estimated to be tens of million dollars during the two months of the study period.

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References

  • Bartlett K, Lee J, Ahmed S et al (2014) Congestion-aware dynamic routing in automated material handling systems. Comput Ind Eng 70:176–182

    Article  Google Scholar 

  • Bazzazi M, Safaei N, Javadian N (2009) A genetic algorithm to solve the storage space allocation problem in a container terminal. Comput Ind Eng 56:44–52. https://doi.org/10.1016/j.cie.2008.03.012

    Article  Google Scholar 

  • Bozer YA, Yen CK (1996) Intelligent dispatching rules for trip-based material handling systems. J Manuf Syst 15:226–239

    Article  Google Scholar 

  • Egbelu PJ (1987) Pull versus push strategy for automated guided vehicle load movement in a batch manufacturing system. J Manuf Syst 6:209–221

    Article  Google Scholar 

  • Egbelu PJ, Tanchoco JMA (1984) Characterization of automatic guided vehicle dispatching rules. Int J Prod Res 22:359–374

    Article  Google Scholar 

  • Frazzon EM, Albrecht A, Pires M et al (2018) Hybrid approach for the integrated scheduling of production and transport processes along supply chains. Int J Prod Res 56:2019–2035. https://doi.org/10.1080/00207543.2017.1355118

    Article  Google Scholar 

  • Hu H, Chen X, Wang T, Zhang Y (2019) A three-stage decomposition method for the joint vehicle dispatching and storage allocation problem in automated container terminals. Comput Ind Eng 129:90–101. https://doi.org/10.1016/j.cie.2019.01.023

    Article  Google Scholar 

  • Im K, Kim K, Park T, Lee S (2009) Effective vehicle dispatching method minimising the blocking and delivery times in automatic material handling systems of 300 mm semiconductor fabrication. Int J Prod Res 47:3997–4011. https://doi.org/10.1080/00207540801914934

    Article  MATH  Google Scholar 

  • Yang J-W, Cheng H-C, Chiang T-C (2008) Li-Chen Fu Multiobjective lot scheduling and dynamic OHT routing in a 300-mm wafer fab. In: 2008 IEEE International Conference on Systems, Man and Cybernetics. IEEE, pp 1608–1613

  • Kim B-I, Oh S, Shin J et al (2007) Effectiveness of vehicle reassignment in a large-scale overhead hoist transport system. Int J Prod Res 45:789–802. https://doi.org/10.1080/00207540600675819

    Article  MATH  Google Scholar 

  • Kim CW, Tanchoco JMA (1991) Conflict-free shortest-time bidirectional AGV routeing. Int J Prod Res 29:2377–2391

    Article  MATH  Google Scholar 

  • Kim CW, Tanchoco JMA, Koo PH (1999) AGV dispatching based on workload balancing. Int J Prod Res 37:4053–4066

    Article  MATH  Google Scholar 

  • Kim H, Lim DE, Lee S (2020) Deep Learning-Based Dynamic Scheduling for Semiconductor Manufacturing with High Uncertainty of Automated Material Handling System Capability. IEEE Trans Semicond Manuf 33:13–22. https://doi.org/10.1109/TSM.2020.2965293

    Article  Google Scholar 

  • Kim J, Yu G, Jang YJ (2016) Semiconductor FAB layout design analysis with 300-mm FAB data: “Is minimum distance-based layout design best for semiconductor FAB design?”. Comput Ind Eng 99:330–346. https://doi.org/10.1016/j.cie.2016.02.012

    Article  Google Scholar 

  • Kim W-S, Lim D-E (2019) On an automated material handling system design problem in cellular manufacturing systems. Eur J Ind Eng 13:400–419

    Article  Google Scholar 

  • Lau HYK, Woo SO (2008) An agent-based dynamic routing strategy for automated material handling systems. Int J Comput Integr Manuf 21:269–288

    Article  Google Scholar 

  • Le-Anh T, De Koster MBM (2005) On-line dispatching rules for vehicle-based internal transport systems. Int J Prod Res 43:1711–1728

    Article  Google Scholar 

  • Lee S, Kim HJ, Kim SB (2020) Dynamic dispatching system using a deep denoising autoencoder for semiconductor manufacturing. Appl Soft Comput J 86:105904. https://doi.org/10.1016/j.asoc.2019.105904

    Article  Google Scholar 

  • Lin JT, Wu CH, Huang CW (2013) Dynamic vehicle allocation control for automated material handling system in semiconductor manufacturing. Comput Oper Res 40:2329–2339

    Article  MATH  Google Scholar 

  • Marandi F, Fatemi Ghomi SMT (2019) Integrated multi-factory production and distribution scheduling applying vehicle routing approach. Int J Prod Res 57:722–748. https://doi.org/10.1080/00207543.2018.1481301

    Article  Google Scholar 

  • Maxwell WL, Muckstadt JA (1982) Design of Automatic Guided Vehicle Systems. A I I E Trans 14:114–124. https://doi.org/10.1080/05695558208975046

  • Min H-S, Yih Y (2003) Selection of dispatching rules on multiple dispatching decision points in real-time scheduling of a semiconductor wafer fabrication system. Int J Prod Res 41:3921–3941. https://doi.org/10.1080/0020754031000118099

    Article  MATH  Google Scholar 

  • Rahman HF, Nielsen I (2019) Scheduling automated transport vehicles for material distribution systems. Appl Soft Comput 82:105552. https://doi.org/10.1016/j.asoc.2019.105552

    Article  Google Scholar 

  • Roser C, Masaru N, Minoru T (2002) Productivity improvement: shifting bottleneck detection. In: the 34th conference of Winter Simulation: exploring new frontiers. pp 1079–1086

  • Siebert M, Bartlett K, Kim H et al (2018) Lot targeting and lot dispatching decision policies for semiconductor manufacturing: optimisation under uncertainty with simulation validation. Int J Prod Res 56:629–641

    Article  Google Scholar 

  • Smolic-Rocak N, Bogdan S, Kovacic Z, Petrovic T (2010) Time windows based dynamic routing in multi-AGV systems. IEEE Trans Autom Sci Eng 7:151–155

    Article  Google Scholar 

  • Taghaboni-Dutta F, Tanchoco JMA (1995) Comparison of dynamic routeing techniques for automated guided vehicle system. Int J Prod Res 33:2653–2669

    Article  MATH  Google Scholar 

  • Wang FK, Lin JT (2004) Performance evaluation of an automated material handling system for a wafer fab. Robot Comput Integr Manuf 20:91–100. https://doi.org/10.1016/j.rcim.2003.08.002

    Article  Google Scholar 

  • Wang FK, Lin JT (2004) Performance evaluation of an automated material handling system for a wafer fab. Robot Comput Integr Manuf 20:91–100. https://doi.org/10.1016/j.rcim.2003.08.002

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Funding

This work was supported by the National Research Foundation of Korea grant funded by the Korea government (No.2019R1G1A1011098).

Conflicts of interest/Competing interests

We have no known conflict of interest to disclose.

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Authors and Affiliations

  1. Department of Industrial and Management Engineering, Korea National University of Transportation (KNUT), 50 Daehak-ro, Daesowon-myeon, 27469, Chungju, Chungbuk, Republic of Korea

    Haejoong Kim & Jongsung Lee

  2. Automated Material Handling Group, Device Solutions Division, Samsung Electronics, 18448, Hwaseong, Gyeonggi, Republic of Korea

    Jeehyuk Park

Authors
  1. Haejoong Kim
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  2. Jeehyuk Park
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  3. Jongsung Lee
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Correspondence to Jongsung Lee.

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Kim, H., Park, J. & Lee, J. Storage prioritization by redistributing wafer lot transfers to enhance real-world fab throughput. Flex Serv Manuf J 35, 599–625 (2023). https://doi.org/10.1007/s10696-022-09449-8

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  • DOI: https://doi.org/10.1007/s10696-022-09449-8

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