在小批量生产的准备时间限制下对集群工具进行调度

Hyun-Jung Kim, Tae-Eog Lee
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引用次数: 9

摘要

我们研究了一个关于小批量生产集群工具的调度问题。大多数关于集群工具调度的工作都假定大量相同的晶圆批,并检查重复相同工作周期的循环调度。然而,现在的批量规模往往非常小,甚至只有5-8片晶圆,而传统的批量有25片相同的晶圆。对于这样的小批量生产,使用循环调度是不合理的,因为与开始和关闭瞬态周期的长度相比,相同工作周期的数量太少了。因此,我们研究了一种新的集群工具调度方法,该方法对腔室和机器人具有就绪时间约束,从而使资源从处理前一批中解放出来。为了解决这一调度问题,我们建立了离散事件动态系统的Petri网模型,这是一种图形化和数学化的方法。基于Petri网模型,我们建立了一个混合整数规划(MIP)模型和一个分支定界(B&B)算法来确定最小化最大工期的最优调度。对于单臂工具,该算法可以有效地解决多达25片晶圆的批次调度问题。然而,对于双臂工具,计算时间随着晶圆数量的增加而迅速增长。因此,我们提出了一种近似的方法,即只对前几个晶圆进行非周期性调度,而对其余晶圆进行周期性调度。从实验中,我们得出结论,近似方法提供了良好的解决方案,误差小于1%。所提出的方法即使在整批25片晶圆频繁切换的情况下也可以使用。
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Scheduling of cluster tools with ready time constraints for small lot production
We examine a scheduling problem regarding cluster tools for small lot production. Most work on scheduling of cluster tools assumed large identical wafer lots, and examined cyclic scheduling that repeats identical work cycles. However, nowadays, the lot size tends to be extremely small, even being only 5–8 wafers whereas conventional lots have 25 identical wafers. It is not reasonable to use cyclic scheduling for such small lot production because the number of identical work cycles is too small as compared to the lengths of the starting and closing transient periods. We therefore examine a new scheduling method for cluster tools with ready time constraints on the chambers and the robot, from which the resources are freed from processing the preceding lot. To solve this scheduling problem, we develop a Petri net model which is a graphical and mathematical method for a discrete event dynamic system. Based on the Petri net model, we develop a mixed integer programming (MIP) model and a branch & bound (B&B) algorithm for determining an optimal schedule that minimizes the makespan. For a single-armed tool, the algorithm can efficiently solve the scheduling problem for lots with up to 25 wafers. However, for a dual-armed tool, the computation time grows quickly as the number of wafers increases. Therefore, we propose an approximate method that schedules only the first few wafers non-cyclically and the remaining wafers cyclically. From experiments, we conclude that the approximate method provides good solutions with less than a 1% error. The proposed methods can be used even when full lots of 25 wafers are frequently switched.
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