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Volume 7 Issue 2
Mar.  2020

IEEE/CAA Journal of Automatica Sinica

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QingHua Zhu, Yan Qiao, NaiQi Wu and Yan Hou, "Post-Processing Time-Aware Optimal Scheduling of Single Robotic Cluster Tools," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 597-605, Mar. 2020. doi: 10.1109/JAS.2020.1003069
Citation: QingHua Zhu, Yan Qiao, NaiQi Wu and Yan Hou, "Post-Processing Time-Aware Optimal Scheduling of Single Robotic Cluster Tools," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 597-605, Mar. 2020. doi: 10.1109/JAS.2020.1003069

Post-Processing Time-Aware Optimal Scheduling of Single Robotic Cluster Tools

doi: 10.1109/JAS.2020.1003069
Funds:  This work was supported in part by the National Natural Science Foundation of China (61673123 , 61803397, 61603100) , Science and Technology Development Fund (FDCT), and Macau SAR of China (0017/2019/ Al, 005/2018/Al, 011/2017/A)
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  • Integrated circuit chips are produced on silicon wafers. Robotic cluster tools are widely used since they provide a reconfigurable and efficient environment for most wafer fabrication processes. Recent advances in new semiconductor materials bring about new functionality for integrated circuits. After a wafer is processed in a processing chamber, the wafer should be removed from there as fast as possible to guarantee its high-quality integrated circuits. Meanwhile, maximization of the throughput of robotic cluster tools is desired. This work aims to perform post-processing time-aware scheduling for such tools subject to wafer residency time constraints. To do so, closed-form expression algorithms are derived to compute robot waiting time accurately upon the analysis of particular events of robot waiting for single-arm cluster tools. Examples are given to show the application and effectiveness of the proposed algorithms.

     

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  • [1]
    S. P. Sethi, J. B. Sidney, and C. Sriskandarajah, “Scheduling in dual gripper robotic cells for productivity gains,” IEEE Trans. Robot. Autom., vol. 17, no. 3, pp. 324–341, Jun. 2001. doi: 10.1109/70.938389
    [2]
    S. Venkatesh, R. Davenport, P. Foxhoven, and J. Nulman, “A steady state throughput analysis of cluster tools: dual-blade versus single-blade robots,” IEEE Trans. Semiconduct. Manufact., vol. 10, no. 4, pp. 418–424, 1997. doi: 10.1109/66.641483
    [3]
    J.-H. Kim and T.-E. Lee, “Schedulability analysis of time-constrained cluster tools with bounded time variation by an extended Petri net,” IEEE Trans. Automat. Sci. Eng., vol. 5, no. 3, pp. 490–503, 2008. doi: 10.1109/TASE.2007.912716
    [4]
    Y. Hou, N. Q. Wu, M. C. Zhou, and Z. W. Li, “Pareto-optimization for scheduling of crude oil operations in refinery via genetic algorithm,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 47, no. 3, pp. 517–530, Mar. 2017. doi: 10.1109/TSMC.2015.2507161
    [5]
    S. W. Zhang, N. Q. Wu, Z. W. Li, T. Qu, and C. D. Li, “Petri net-based approach to short-term scheduling of crude oil operations with less tank requirement,” Inform. Sciences, vol. 417, pp. 247–261, Nov. 2017. doi: 10.1016/j.ins.2017.07.009
    [6]
    N. Q. Wu, M. C. Zhou, and Z. W. Li, “Short-term scheduling of crude-oil operations: Petri net-based control-theoretic approach,” IEEE Robot. Autom. Mag., vol. 22, no. 2, pp. 64–76, Jun. 2015. doi: 10.1109/MRA.2015.2415047
    [7]
    N. Q. Wu, M. C. Zhou, L. P. Bai, and Z. W. Li, “Short-term scheduling of crude oil operations in refinery with high fusion point oil and two transportation pipelines,” Enterp. Inf. Syst., vol. 10, no. 6, May 2016.
    [8]
    L. P. Bai, N. Q. Wu, Z. W. Li, and M. C. Zhou, “Optimal one-wafer cyclic scheduling and buffer space configuration for single-arm multicluster tools with linear topology,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 46, no. 10, pp. 1456–1467, Oct. 2016. doi: 10.1109/TSMC.2015.2501232
    [9]
    W. K. Chan, J. G. Yi, and S. W. Ding, “Optimal scheduling of multi-cluster tools with constant robot moving times, part i: two-cluster analysis,” IEEE Trans. Automat. Sci. Eng., vol. 8, no. 1, pp. 5–16, Jan. 2011. doi: 10.1109/TASE.2010.2046891
    [10]
    M. Dawande, C. Sriskandarajah, and S. P. Sethi, “On throughput maximization in constant travel-time robotic cells,” Manufact. Serv. Oper. Manage, vol. 4, no. 4, pp. 296–312, 2002. doi: 10.1287/msom.4.4.296.5731
    [11]
    H. N. Geismar, M. Dawande, and S. Chelliah, “Robotic cells with parallel machines: throughput maximization in constant travel-time cells,” J. Scheduling, vol. 7, no. 5, pp. 375–395, 2004. doi: 10.1023/B:JOSH.0000036861.28456.5d
    [12]
    D. B. Jevtic, M. A. Pool, and R. S. Sunkara,“Method and apparatus for managing scheduling a multiple cluster tool,” European Patent. vol. 1, 132, 792(A2) European: Applied Materials Inc., 2001.
    [13]
    D.-K. Kim, H.-J. Kim, and T.-E. Lee, “Optimal scheduling for sequentially connected cluster tools with dual-armed robots and a single input and output module,” Int. J. Product. Res., vol. 55, no. 11, pp. 3092–3109, 2017. doi: 10.1080/00207543.2016.1243819
    [14]
    J.-H. Lee and H.-J. Kim, “Completion time analysis of wafer lots in single-armed cluster tools with parallel processing modules,” IEEE Trans. Automat. Sci. Eng., vol. 14, no. 4, pp. 1622–1633, 2017. doi: 10.1109/TASE.2017.2690443
    [15]
    X. Li and R. Y. K. Fung, “Optimal K-unit cycle scheduling of two-cluster tools with residency constraints and general robot moving times,” J. Scheduling, vol. 19, no. 2, pp. 165–176, Apr. 2016. doi: 10.1007/s10951-015-0448-7
    [16]
    T. Nishi and I. Matsumoto, “Petri net decomposition approach to deadlock-free and non-cyclic scheduling of dual-armed cluster tools,” IEEE Trans. Automat. Sci. Eng., vol. 12, no. 1, pp. 281–294, Jan. 2015. doi: 10.1109/TASE.2013.2292572
    [17]
    N. Q. Wu and M. C. Zhou, System Modeling and Control With Resource-oriented Petri Nets. Boca Raton, FL, USA: CRC Press, Inc., 2009.
    [18]
    T. Nishi, Y. Watanabe, and M. Sakai, “An efficient deadlock prevention policy for noncyclic scheduling of multicluster tools,” IEEE Trans. Automat. Sci. Eng., vol. 15, no. 4, pp. 1677–1691, Oct. 2018. doi: 10.1109/TASE.2017.2771751
    [19]
    K. Park and J. R. Morrison, “Controlled wafer release in clustered photolithography tools: flexible flow line job release scheduling and an LMOLP heuristic,” IEEE Trans. Automat. Sci. Eng., vol. 12, no. 2, pp. 642–655, Apr. 2015. doi: 10.1109/TASE.2014.2311997
    [20]
    F. J. Yang, N. Q. Wu, Y. Qiao, and R. Su, “Polynomial approach to optimal one-wafer cyclic scheduling of treelike hybrid multi-cluster tools via Petri nets,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 270–280, Mar. 2018. doi: 10.1109/JAS.2017.7510772
    [21]
    Q. H. Zhu, Y. Qiao, and N. Q. Wu, “Optimal integrated schedule of entire process of dual-blade multi-cluster tools from start-up to close-down,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 553–565, Mar. 2019. doi: 10.1109/JAS.2019.1911411
    [22]
    Q. H. Zhu, N. Q. Wu, Y. Qiao, and M. C. Zhou, “Scheduling of single-arm multi-cluster tools with wafer residency time constraints in semiconductor manufacturing,” IEEE Trans. Semiconduct. Manufact., vol. 28, no. 1, pp. 117–125, 2015. doi: 10.1109/TSM.2014.2375880
    [23]
    Q. H. Zhu, M. C. Zhou, Y. Qiao, and N. Q. Wu, “Scheduling transient processes for time-constrained single-arm robotic multi-cluster tools,” IEEE Trans. Semiconduct. Manufact., vol. 30, no. 3, pp. 261–269, Aug. 2017. doi: 10.1109/TSM.2017.2721970
    [24]
    H.-J. Kim and J.-H. Lee, “Closed-form expressions on lot completion time for dual-armed cluster tools with parallel processing modules,” IEEE Trans. Automat. Sci. Eng., vol. 16, no. 2, pp. 898–907, Apr. 2019. doi: 10.1109/TASE.2018.2874664
    [25]
    C. Sriskandarajah, I. Drobouchevitch, and S. P. Sethi, “Scheduling multiple parts in a robotic cell served by a dual-gripper robot,” Oper. Res., vol. 52, no. 1, pp. 65–82, 2004. doi: 10.1287/opre.1030.0073
    [26]
    H. J. Yoon and D. Y. Lee, “Online scheduling of integrated single-wafer processing tools with temporal constraints,” IEEE Trans. Semiconduct. Manufact., vol. 18, no. 3, pp. 390–398, Aug. 2005. doi: 10.1109/TSM.2005.852103
    [27]
    F. J. Yang, N. Q. Wu, Y. Qiao, M. C. Zhou, and Z. W. Li, “Scheduling of single-arm cluster tools for an atomic layer deposition process with residency time constraints,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 47, no. 3, pp. 502–516, Mar. 2017. doi: 10.1109/TSMC.2015.2507140
    [28]
    N. Q. Wu, F. Chu, C. B. Chu, and M. C. Zhou, “Petri net modeling and cycle-time analysis of dual-arm cluster tools with wafer revisiting,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 43, no. 1, pp. 196–207, 2013. doi: 10.1109/TSMCA.2012.2187890
    [29]
    W. M. Zuberek, “Timed Petri nets in modeling and analysis of cluster tools,” IEEE Trans. Robot. Autom, vol. 17, no. 5, pp. 562–575, Oct. 2001. doi: 10.1109/70.964658
    [30]
    J.-H. Kim, T.-E. Lee, H.-Y. Lee, and D.-B. Park, “Scheduling analysis of time-constrained dual-armed cluster tools,” IEEE Trans. Semiconduct. Manufact., vol. 16, no. 8, pp. 521–534, Aug. 2003.
    [31]
    T.-E. Lee and S.-H. Park, “An extended event graph with negative places and tokens for timed window constraints,” IEEE Trans. Automat. Sci. Eng., vol. 2, no. 4, pp. 319–332, 2005. doi: 10.1109/TASE.2005.851236
    [32]
    N. Q. Wu, C. B. Chu, F. Chu, and M. C. Zhou, “A petri net method for schedulability and scheduling problems in single-arm cluster tools with wafer residency time constraints,” IEEE Trans. Semiconduct. Manufact., vol. 21, no. 2, pp. 224–237, May 2008. doi: 10.1109/TSM.2008.2000425
    [33]
    N. Q. Wu and M. C. Zhou, “A closed-form solution for schedulability and optimal scheduling of dual-arm cluster tools with wafer residency time constraint based on steady schedule analysis,” IEEE Trans. Automat. Sci. Eng., vol. 7, no. 2, pp. 303–315, Apr. 2010. doi: 10.1109/TASE.2008.2008633
    [34]
    N. Q. Wu and M. C. Zhou, “Modeling, analysis and control of dual-arm cluster tools with residency time constraint and activity time variation based on Petri nets,” IEEE Trans. Automat. Sci. Eng., vol. 9, no. 2, pp. 446–454, Apr. 2012. doi: 10.1109/TASE.2011.2178023
    [35]
    N. Q. Wu and M. C. Zhou, “Schedulability analysis and optimal scheduling of dual-arm cluster tools with residency time constraint and activity time variation,” IEEE Trans. Automat. Sci. Eng., vol. 9, no. 1, pp. 203–209, Jan. 2012. doi: 10.1109/TASE.2011.2160452
    [36]
    J.-H. Paek and T.-E. Lee, “Optimal scheduling of dual-armed cluster tools without swap restriction,” in Proc. IEEE Int. Conf. Auto. Sci. Eng., Washington DC, USA, 2008, pp. 103–108.
    [37]
    X. W. Guo, S. X. Liu, M. C. Zhou, and G. D. Tian, “Disassembly sequence optimization for large-scale products with multiresource constraints using scatter search and Petri nets,” IEEE Trans. Cybern., vol. 46, no. 11, pp. 2435–2446, Nov. 2016. doi: 10.1109/TCYB.2015.2478486
    [38]
    B. Huang, M. C. Zhou, P. Y. ZHang, and J. Yang, “Speedup techniques for multiobjective integer programs in designing optimal and structurally simple supervisors of AMS,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 1, pp. 77–88, Jan. 2018. doi: 10.1109/TSMC.2016.2587671
    [39]
    H.-Y. Jin and J. R. Morrison, “Transient scheduling of single armed cluster tools: Algorithms for wafer residency constraints,” in Proc. IEEE Int. Conf. Auto. Sci. Eng., Madison, WI, USA, 2013, pp. 856–861.
    [40]
    J. G. Yi, S. W. Ding, D. Z. Song, and M. T. Zhang, “Steady-state throughput and scheduling analysis of multi-cluster tools for semiconductor manufacturing: a decomposition approach,” IEEE Trans. Automat. Sci. Eng., vol. 5, no. 2, pp. 321–336, 2008. doi: 10.1109/TASE.2007.906678
    [41]
    H.-J. Kim, J.-H. Lee, C. Jung, and T.-E. Lee, “Scheduling cluster tools with ready time constraints for consecutive small lots,” IEEE Trans. Automat. Sci. Eng., vol. 10, no. 1, pp. 145–159, 2013. doi: 10.1109/TASE.2012.2220355
    [42]
    J.-H. Lee, H.-J. Kim, and T.-E. Lee, “Scheduling lot switching operations for cluster tools,” IEEE Trans. Semiconduct. Manufact., vol. 26, no. 4, pp. 592–601, 2013. doi: 10.1109/TSM.2013.2281083
    [43]
    A. Davenport, “Integrated maintenance scheduling for semiconductor manufacturing,” in Proc. 7th Int. Conf. CPAIOR, Bologna, Italy, 2010, pp. 92–96.
    [44]
    J. A. Ramírez-Hernández, J. Crabtree, X. D. Yao, E. Fernandez, M. C. Fu, M. Janakiram, S. I. Marcus, M. O'Connor, and N. Patel, “Optimal preventive maintenance scheduling in semiconductor manufacturing systems: software tool and simulation case studies,” IEEE Trans. Semiconduct. Manufact., vol. 23, no. 3, pp. 477–489, Aug. 2010. doi: 10.1109/TSM.2010.2051731
    [45]
    D.-K. Kim, T.-E. Lee, and H.-J. Kim, “Optimal scheduling of transient cycles for single-armed cluster tools with parallel chambers,” IEEE Trans. Automat. Sci. Eng., vol. 13, no. 2, pp. 1165–1175, Apr. 2016. doi: 10.1109/TASE.2015.2443107
    [46]
    T.-K. Kim, C. Junga, and T.-E. Lee, “Scheduling start-up and close-down periods of dual-armed cluster tools with wafer delay regulation,” Int. J. Product. Res., vol. 50, no. 10, pp. 2785–2795, May 2012. doi: 10.1080/00207543.2011.590949
    [47]
    Y. Qiao, N. Q. Wu, F. J. Yang, M. C. Zhou, and Q. H. Zhu, “Wafer sojourn time fluctuation analysis of time-constrained dual-arm cluster tools with wafer revisiting and activity time variation,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 4, pp. 622–636, Apr. 2018. doi: 10.1109/TSMC.2016.2600583
    [48]
    Y. Qiao, M. C. Zhou, N. Q. Wu, and Q. H. Zhu, “Scheduling and control of startup process for single-arm cluster tools with residency time constraints,” IEEE Trans. Control Syst. Technol., vol. 25, no. 4, pp. 1243–1256, Jul. 2017. doi: 10.1109/TCST.2016.2598762
    [49]
    Q. H. Zhu, M. C. Zhou, Y. Qiao, and N. Q. Wu, “Petri net modeling and scheduling of a close-down process for time-constrained single-arm cluster tools,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 3, pp. 389–400, Mar. 2018. doi: 10.1109/TSMC.2016.2598303
    [50]
    H.-J. Kim, J.-H. Lee, and T.-E. Lee, “Schedulability analysis for noncyclic operation of time-constrained cluster tools with time variation,” IEEE Trans. Automat. Sci. Eng., vol. 13, no. 3, pp. 1409–1414, Jul. 2016. doi: 10.1109/TASE.2016.2531105
    [51]
    M. Meyyappan, “A review of plasma enhanced chemical vapour deposition of carbon nanotubes,” J. Phys. D:Appl. Phys., vol. 42, no. 21, pp. 213001–213015, 2009. doi: 10.1088/0022-3727/42/21/213001
    [52]
    R. Muñoz and C. Gómez-Aleixandre, “Review of CVD synthesis of graphene,” Chem. Vap. Deposition, vol. 19, no. 10-11-12, pp. 297–322, Dec. 2013. doi: 10.1002/cvde.201300051
    [53]
    W. Liu, S. Kraemer, D. Sarkar, H. Li, P. M. Ajayan, and K. Banerjee, “Controllable and rapid synthesis of high-quality and large-area Bernal stacked bilayer graphene using chemical vapor deposition,” Chem. Mater., vol. 26, no. 2, pp. 907–915, Dec. 2013.
    [54]
    I. Drobouchevitch, S. P. Sethi, and C. Sriskandarajah, “Scheduling dual gripper robotic cells: one-unit cycles,” Eur. J. Oper. Res., vol. 171, no. 2, pp. 598–631, Jun. 2006. doi: 10.1016/j.ejor.2004.09.019
    [55]
    X. W. Guo, S. X. Liu, M. C. Zhou, and G. D. Tian, “Dual-objective program and scatter search for the optimization of disassembly sequences subject to multi-resource constraints,” IEEE Trans. Automat. Sci. Eng., vol. 15, no. 3, pp. 1091–1013, Jul. 2018. doi: 10.1109/TASE.2017.2731981
    [56]
    X. H. Meng, J. Li, M. C. Zhou, X. Z. Dai, and J. P. Dou, “Population-based incremental learning algorithm for a serial colored traveling salesman problem,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 2, pp. 277–288, Feb. 2018. doi: 10.1109/TSMC.2016.2591267
    [57]
    J. Zhao, S. X. Liu, M. C. Zhou, X. W. Guo, and L. Qi, “Modified cuckoo search algorithm to solve economic power dispatch optimization problems,,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 4, pp. 794–806, May 2018. doi: 10.1109/JAS.2018.7511138
    [58]
    J. Zhao, S. X. Liu, M. C. Zhou, X. W. Guo, and L. Qi, “An improved binary cuckoo search algorithm for solving unit commitment problem: method description,” IEEE Access, vol. 6, no. 4, pp. 43535–43545, May 2018.

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    Highlights

    • High-quality integrated circuits (ICs) are expected in semiconductor manufacturing.
    • High quality of ICs is sensitive to a wafer's post-processing time.
    • This work aims to perform post-processing time-aware scheduling for cluster tools.
    • Efficient algorithms are proposed to achieve high productivity and quality.

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