Optimal Integrated Schedule of Entire Process of Dual-blade Multi-cluster Tools From Start-up to Close-down

Qinghua Zhu; Yan Qiao; Naiqi Wu

doi:10.1109/JAS.2019.1911411

Volume 6 Issue 2

Mar. 2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2019 > 6(2): 553-565

Qinghua Zhu, Yan Qiao and Naiqi 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

Citation:

Qinghua Zhu, Yan Qiao and Naiqi 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

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Optimal Integrated Schedule of Entire Process of Dual-blade Multi-cluster Tools From Start-up to Close-down

doi: 10.1109/JAS.2019.1911411

Qinghua Zhu^{1, 2
,},
Yan Qiao^3
,,
Naiqi Wu^{3, 4
,
,}

1.
School of Computer Science and Technology, Guangdong University of Technology, Guangzhou 510006, China
2.
Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark NJ 07102, USA
3.
Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau, China
4.
National Key Laboratory of Precise Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China

Funds:

National Natural Science Foundation of China 61673123

National Natural Science Foundation of China 61803397

the Science and Technology Development Fund (FDCT) of Macau 106/2016/A3

the Science and Technology Development Fund (FDCT) of Macau 005/2018/A1

the Science and Technology Development Fund (FDCT) of Macau 011/2017/A

the Science and Technology Development Fund (FDCT) of Macau 0017/2019/A1

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Author Bio:
Qinghua Zhu (M'15-SM'17) received the Ph.D. degree in industrial engineering from Guangdong University of Technology, China, in 2013. During Oct. 2014 through Sep. 2015, and Sep. 2017 through Aug. 2018, he was a Visiting Scholar with the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA. He joined Guangdong University of Technology, Guangzhou, China in 2003, and is currently an Associate Professor with the School of Computer Science and Technology. His research interests include scheduling and optimization, discrete event systems, and Petri nets.(e-mail: zhuqh@gdut.edu.cn)

Yan Qiao (M'16) received the B.S. and Ph.D. degrees in industrial engineering and mechanical engineering from Guangdong University of Technology, Guangzhou, China, in 2009 and 2015, respectively. From Sep. 2014 to Sep. 2015, he was a Visiting Student with the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA. From Jan. 2016 to Dec. 2017, he was a Post-Doctoral Research Associate with the Institute of Systems Engineering, Macau University of Science and Technology. Since Jan. 2018, he is an assistant professor at Macau University of Science and Technology. He has over 50 publications, including one book chapter and over 30 international journal papers. His research interests include discrete event systems, production planning, Petri nets, scheduling and control. Dr. Qiao was a recipient of the QSI Best Application Paper Award Finalist of 2011 IEEE International Conference on Automation Science and Engineering, the Best Student Paper Award of 2012 IEEE International Conference on Networking, Sensing and Control, and the Best Conference Paper Award Finalist of 2016 IEEE International Conference on Automation Science and Engineering. He has served as a reviewer for a number of journals.(e-mail:yqiao@must.edu.mo)

Naiqi Wu (M'04-SM'05-F'19) received the B.S. degree in electrical engineering from Anhui University of Technology, Huainan, China, in 1982, the M.S. and Ph.D. degrees in systems engineering both from Xi'an Jiaotong University, Xi'an, China in 1985 and 1988, respectively. From 1988 to 1995, he was with Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, and from 1995 to 1998, with Shantou University, Shantou, China. He moved to Guangdong University of Technology, Guangzhou, China in 1998. He joined Macau University of Science and Technology in 2013. He was a Visiting Professor at Arizona State University, Tempe, USA, in 1999; New Jersey Institute of Technology, Newark, USA, in 2004; University of Technology of Troyes, Troyes, France, from 2007 to 2009; and Evry University, Evry, France, from 2010 to 2011. He is currently a Professor at the Institute of Systems Engineering, Macau University of Science and Technology. His research interests include production planning and scheduling, manufacturing system modeling and control, discrete event systems, Petri net theory and applications, intelligent transportation systems, and energy systems. He is the author or coauthor of one book, five book chapters, and 140+ peer-reviewed journal papers. Dr. Wu was an Associate Editor of the IEEE Transactions on Systems, Man, & Cybernetics, Part C, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Systems, Man, & Cybernetics: Systems, and an Editor in Chief of Industrial Engineering Journal, and is an Associate Editor of Information Sciences and IEEE/CAA Journal of Automatica Sinica.(e-mail: nqwu@must.edu.mo)
Corresponding author: Naiqi Wu, e-mail: nqwu@must.edu.mo
Received Date: 2018-10-28
Accepted Date: 2018-11-19

Abstract

Abstract

Multi-cluster tools are widely used in majority of wafer fabrication processes in semiconductor industry. Smaller lot production, thinner circuit width in wafers, larger wafer size, and maintenance have resulted in a large quantity of their start-up and close-down transient periods. Yet, most of existing efforts have been concentrated on scheduling their steady states. Different from such efforts, this work schedules their transient and steady-state periods subject to wafer residency constraints. It gives the schedulability conditions for the steady-state scheduling of dual-blade robotic multi-cluster tools and a corresponding algorithm for finding an optimal schedule. Based on the robot synchronization conditions, a linear program is proposed to figure out an optimal schedule for a start-up period, which ensures a tool to enter the desired optimal steady state. Another linear program is proposed to find an optimal schedule for a close-down period that evolves from the steady state period. Finally, industrial cases are presented to illustrate how the provided method outperforms the existing approach in terms of system throughput improvement.
- Multi-cluster tools,
- robots,
- scheduling transient periods,
- semiconductor manufacturing systems

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References

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Optimal Integrated Schedule of Entire Process of Dual-blade Multi-cluster Tools From Start-up to Close-down

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