Robot Waiting Time Analysis and Its Impact on Wafer Delay Time of Single-Arm Cluster Tools

Xiong, WenQing; Qiao, Yan; Wu, Naiqi; Bai, Liping; Chen, MingXin; Hsieh, PinHui; Yin, Li

doi:10.1016/j.ifacol.2021.04.056

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Recall that 𝜋 𝑗 is the system cycle time of job j during steady state. We obtain from Xiong et al (2020) the following result for the waiting time.…”

Section: Calculation For the Remaining Processing Timementioning

confidence: 90%

“…Closed-form scheduling algorithms are designed to compute optimal schedules. A backward earliest-starting strategy (BESS) is proposed by Xiong et al (2020). The robot waiting time is analyzed under steady-state conditions.…”

Section: Internal Ct Scheduling Approachesmentioning

confidence: 99%

“…Proof: A proof of the statements directly follows from Theorems 3.1 and 3.2 in Xiong et al (2020). Although identical recipes are assumed by Xiong et al (2020), this assumption is not used in the proofs since steady-state conditions are assumed.…”

Section: Calculation For the Remaining Processing Timementioning

confidence: 99%

See 2 more Smart Citations

An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

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2024

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Cluster tools are integrated machines for wafer processing in semiconductor wafer fabrication facilities (wafer fabs). Since different kinds of wafers can circulate in a cluster tool simultane-ously, it is a fully automated machine environment. The development of scheduling ap-proaches for these extremely expensive machines is essential for improving their operations. We study a scheduling problem on the work center level, i.e. for parallel cluster tools. The performance measure is the total weighted tardiness. All jobs are available at scheduling time. Two different biased random-key genetic algorithms (BRKGAs) are designed to assign jobs to cluster tools and to compute sequences for each single cluster tool. We establish algorithms to compute the time a job spent in a cluster tool, called processing time, given the sequence in which the jobs are processed there. They are embedded into the BRKGAs. Computational ex-periments based on randomly generated problem instances are carried out. The results demon-strate that the proposed metaheuristics perform well with respect to solution quality and com-puting time.

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“…Recall that 𝜋 𝑗 is the system cycle time of job j during steady state. We obtain from Xiong et al (2020) the following result for the waiting time.…”

Section: Calculation For the Remaining Processing Timementioning

confidence: 90%

Section: Internal Ct Scheduling Approachesmentioning

confidence: 99%

See 1 more Smart Citation

An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

YANG,

Mönch

2024

Preprint

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show abstract

Cycle time analysis for cluster tools with parallel process chambers, processing time variation, and chamber cleaning operations

Pan,

Lai,

Qiao

et al. 2024

Expert Systems with Applications

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An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

YANG

2024

Preprint

View full text Add to dashboard Cite

Cluster tools are integrated machines for wafer processing in semiconductor wafer fabrication facilities (wafer fabs). Since different kinds of wafers can circulate in a cluster tool simultaneously, it is a fully automated machine environment. The development of scheduling approaches for these extremely expensive machines is essential for improving their operations. We study a scheduling problem on the work center level, i.e. for parallel cluster tools. The performance measure is the total weighted tardiness. All jobs are available at scheduling time. Two different biased random-key genetic algorithms (BRKGAs) are designed to assign jobs to cluster tools and to compute sequences for each single cluster tool. We establish algorithms to compute the time a job spent in a cluster tool, called processing time, given the sequence in which the jobs are processed there. They are embedded into the BRKGAs. Computational experiments based on randomly generated problem instances are carried out. The results demonstrate that the proposed metaheuristics perform well with respect to solution quality and computing time.

show abstract

Robot Waiting Time Analysis and Its Impact on Wafer Delay Time of Single-Arm Cluster Tools

Cited by 3 publications

References 25 publications

An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

Cycle time analysis for cluster tools with parallel process chambers, processing time variation, and chamber cleaning operations

An Integrated Method for External and Internal Scheduling of Parallel Cluster Tools

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