Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88431
Title: Efficient approach to cyclic scheduling of single-arm cluster tools with chamber cleaning operations and wafer residency time constraint
Authors: Yang, Fajun
Wu, Naiqi
Gao, Kaizhou
Zhang, Chunjiang
Zhu, Yuting
Su, Rong
Qiao, Yan
Keywords: Cluster Tools
Wafer Manufacturing
Issue Date: 2018
Source: Yang, F., Wu, N., Gao, K., Zhang, C., Zhu, Y., Su R., & Qiao, Y. (2018). Efficient approach to cyclic scheduling of single-arm cluster tools with chamber cleaning operations and wafer residency time constraint. IEEE Transactions on Semiconductor Manufacturing, 31(2), 196-205. doi: 10.1109/TSM.2018.2811125
Series/Report no.: IEEE Transactions on Semiconductor Manufacturing
Abstract: In semiconductor manufacturing, with the shrinking down of wafer circuit widths, a strict quality control is required for wafer fabrication processes, resulting in that after a wafer being processed and removed from a chamber, a cleaning operation that takes significant time is performed for eliminating the chemical residual. Such a cleaning operation makes a traditional backward strategy for single-arm cluster tools inefficient. By the existing studies, it is shown that the productivity can be improved if some numbers of chambers at a step are kept empty. With this idea, an extended backward strategy is proposed by deciding the optimal number of empty chambers. Based on such a strategy, this work studies the challenging problem for scheduling a single-arm cluster tool with both chamber cleaning operations and wafer residency time constraint for the first time. By building a timed Petri net model for the system, two linear programs are proposed to determine the minimal cycle time and test the existence of a feasible schedule and find it if existing. At last, two industrial examples are used to demonstrate the obtained results.
URI: https://hdl.handle.net/10356/88431
http://hdl.handle.net/10220/44649
ISSN: 0894-6507
DOI: 204677
204677
204677
10.1109/TSM.2018.2811125
204677
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TSM.2018.2811125].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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