Modeling and scheduling of single-armed cluster tools with mixed wafer flows

doi:10.16731/j.cnki.1671-3133.2017.01.006

Abstract

Abstract: For improving the efficiency of cluster tools availably,the issues for processing different types of wafers concurrently in single-armed cluster tools are studied.A Petri net model describing the process of the single-armed cluster tools precisely,which is independent of diverse wafer flow pattern,is developed.Some equations,which define that the single-armed cluster tools is capable of performing a steady and cyclic operation under mixed wafer flows,are derived based on backward and cyclic scheduling strategy.Furthermore,the linear programming model is established and a periodic steady-state schedule is obtained as well.The presented scheduling is executed by the means of virtual wafer and the Gantt chart of scheduling is provided.Finally,the validity and efficiency of the proposed model and scheduling is verified.

Key words: cluster tools, Petri net, modeling, scheduling, wafer fabrication

CLC Number:

TN305

Pan Chunrong, Wang Jipeng, Li Liang. Modeling and scheduling of single-armed cluster tools with mixed wafer flows[J]. Modern Manufacturing Engineering, 2017, 436(1): 29-34.

References

[1] LEE T E.A review of scheduling theory and methods for semiconductor manufacturing cluster tools.Proceedings of the 40th conference on winter simulation[C].Piscataway,USA: IEEE,2008: 2127-2135.
[2] BADER M E,HALL R P,STRASSER G.Integrated processing equipment[J].Solid State Technology,1990,33(5): 149-154.
[3] BURGGRAAF P.Coping with the high cost of wafer fabs[J].Semiconductor International,1995,18(3): 45-54.
[4] PERKINSON T L,MCLARTY P K,GYURCSIK R S,et al.Single-wafer cluster tool performance: An analysis of throughput[J].IEEE Transactions on Semiconductor Manufacturing,1994,7(3):369-373.
[5] PERKINSON T L,GYURCSIK R S,MCLARTY P K.Single-wafer cluster tool performance: An analysis of the effects of redundant chambers and revisitation sequences on throughput[J].IEEE Transactions on Semiconductor Manufacturing,1996,9(3):384-400.
[6] ROSTAMI S,HAMIDZADEH B,CAMPORESE D.An optimal periodic scheduler for dual-arm robots in cluster tools with residency constraints[J].IEEE Transactions on Robotics and Automation,2001,17(5):609-618.
[7] ROSTAMI S,HAMIDZADEH B.Optimal scheduling techniques for cluster tools with process-module and transport-module residency constraints[J].IEEE Transactions on Semiconductor Manufacturing,2002,15(3): 341-349.
[8] WU N Q,CHU C B,CHU F,et al.A Petri net method for schedulability and scheduling problems in single-arm cluster tools with wafer residency time constraints[J].IEEE Transactions on Semiconductor Manufacturing,2008,21(2):224-237.
[9] WU N Q,ZHOU M C.A closed-form solution for schedulability and optimal scheduling of dual-arm cluster tools with wafer residency time constraint based on steady schedule analysis[J].IEEE Transactions on Automation Science and Engineering,2010,7(2): 303-315.
[10] KIM J H,LEE T E.Schedulability analysis of time-constrained cluster tools with bounded time variation by an extended Petri net[J].IEEE Transactions on Automation Science and Engineering,2008,5(3): 490-503.
[11] QIAO Y,WU N Q,ZHOU M C.Real-time scheduling of single-arm cluster tools subject to residency time constraints and bounded activity time variation[J].IEEE Transactions on Automation Science and Engineering,2012,9(3):564-577.
[12] LEE J H,KIM H J,LEE T E.Scheduling Cluster Tools for Concurrent Processing of Two Wafer Types[J].IEEE Transactions on Automation Science and Engineering,2014,11(2):525-536.
[13] 郑秀红,胡静涛,于海斌.基于随机Petri网的集束型装备模型及Markov分析[J].信息与控制,2011,40 (4) : 472-476.

[1]	XIA Liangcai, CHEN Shijun. Co-evolution algorithm based on Dueling-DQN for solving green distributed heterogeneous flexible job shop scheduling problem [J]. Modern Manufacturing Engineering, 2025, 538(7): 8-19.
[2]	ZHANG Ningning, WAN Weibing, ZHANG Mengxiao, ZHAO Yuming. Research on reinforcement learning decision algorithm for multi-objective dynamic job shop scheduling [J]. Modern Manufacturing Engineering, 2025, 538(7): 20-30.
[3]	WANG Lei, LIU Xinlan, GUO Yuyao, ZHANG Zelin, XIA Xuhui. Fusion semantic information modeling method of waste mechanical product [J]. Modern Manufacturing Engineering, 2025, 538(7): 80-88.
[4]	LIAO Xuechao, XIANG Guihong, RUAN Bing, TIAN Ruili, ZHONG Shi. Research on flexible job-shop scheduling problem with AGV quantity constraints [J]. Modern Manufacturing Engineering, 2025, 537(6): 11-21.
[5]	LIU Quanquan, FANG Xifeng, CHENG Dejun, QI Jie, LI Xiaoyan, SU Jiabao, LUO Lanzhen. Research on the digital definition technology of cabin products based on MBD [J]. Modern Manufacturing Engineering, 2025, 537(6): 22-29.
[6]	HE Xinrong, SHAO Feng, GUO Jia, DU Xiaoze. IPNCC-MCSKNet-based voiceprint recognition of rolling bearing faults under variable operating conditions [J]. Modern Manufacturing Engineering, 2025, 536(5): 135-143.
[7]	LIU Jinfei, LIU Yihan, CHEN Ming, HUANG Hua. Intelligent workshop scheduling with multiple varieties and variable batches based on improved IGA [J]. Modern Manufacturing Engineering, 2025, 535(4): 1-10.
[8]	CHEN Ziyan, LI Zengcan, GUAN Zailin. Research on flexible job shop batch scheduling problem with variable sublots based on improved sparrow search algorithm [J]. Modern Manufacturing Engineering, 2025, 535(4): 11-24.
[9]	XU Shuai, LI Yanwu, XIE Hui, NIU Xiaowei. The PPO algorithm based on convolutional pyramid network to solve job-shop scheduling problem [J]. Modern Manufacturing Engineering, 2025, 534(3): 19-30.
[10]	WANG Chun, ZHANG Chaoyang, JI Weixi, LU Jingyu. Research on optimization of production scheduling in discrete workshops considering equipment degradation [J]. Modern Manufacturing Engineering, 2025, 534(3): 31-40.
[11]	LIU Liang, HE Yuming, QI Siyuan. Optimization study of flexible job-shop scheduling based on digital twin simulation [J]. Modern Manufacturing Engineering, 2025, 534(3): 41-51.
[12]	YANG Dan, SHU Xiantao, YU Zhen, LU Guangtao, JI Songlin, WANG Jiabing. A dynamic flexible job shop scheduling method based on deepreinforcement learning [J]. Modern Manufacturing Engineering, 2025, 533(2): 10-16.
[13]	ZHOU Guocheng, TAO Yifei, HE Yi, LI Lishan, WU Jiaxing. Research on the online scheduling problem of multi-AGVs in automatic packing system [J]. Modern Manufacturing Engineering, 2025, 533(2): 17-25.
[14]	YANG Fenghai, YANG Xiaoying, PEI Zhijie, WU Yaqi, ZHANG Zhiwei. Deep reinforcement learning for production intelligent scheduling of wind turbine extrusion panels [J]. Modern Manufacturing Engineering, 2025, 532(1): 23-32.
[15]	HUO Junjie, WANG Zhijian. Process planning and workshop scheduling integrated optimization adopting new coding mode genetic algorithm [J]. Modern Manufacturing Engineering, 2024, 528(9): 25-33.