An Efficient Scheduling Method for Single-Arm Cluster Tools With Multifunctional Process Modules

Nowadays, cluster tools are extensively used for many wafer manufacturing processes, such as coating, lithograph, developing, etching, deposition, and testing. Traditional process modules in cluster tools can execute a single operation only. With the rapid development of equipment design, multifunct...

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Bibliographic Details
Published inIEEE transactions on systems, man, and cybernetics. Systems Vol. 53; no. 6; pp. 3270 - 3283
Main Authors Xiong, WenQing, Li, Jie, Qiao, Yan, Bai, LiPing, Huang, BaoYing, Wu, NaiQi
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Cleaning
Cluster tools
Clusters
Coatings
Load modeling
Mathematical models
Modules
optimization
Petri nets
Process parameters
Productivity
Robots
Schedules
Scheduling
Semiconductor device modeling
semiconductor manufacturing
Task analysis
wafer fabrication
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Summary:Nowadays, cluster tools are extensively used for many wafer manufacturing processes, such as coating, lithograph, developing, etching, deposition, and testing. Traditional process modules in cluster tools can execute a single operation only. With the rapid development of equipment design, multifunctional process modules (MPMs) are equipped to serve for processing multiple operations together just like a single operation. With different wafer processing parameters, MPMs may be set for processing multiple operations together or processing just a single operation to form different schedules so as to maximize the productivity. Thus, it is highly desired to find an efficient scheduling method to quickly adapt to wafer processing parameter changes for productivity maximization by taking the advantages of MPMs. To tackle this issue, a deadlock-free Petri net (PN) model is developed to describe the behavior of a single-arm cluster tool. Based on the evolving mechanism of the PN model, two algorithms are developed to calculate the makespan for completing a given number of wafers. Then, an adaptive scheduling method is presented to set the functions of MPMs to minimize the makespan. Finally, experimental results show the efficiency and effectiveness of the proposed method.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2022.3222915