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Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals

机译:具有不兼容的作业族和将来的作业到达的单批处理器的控制

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摘要

We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered $f$, and the number of future job arrivals $L$. Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computat ional costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy.
机译:我们研究了在不兼容的工作族和将来的工作到达时,使批处理机的平均周期时间最小化的问题。在晶圆制造中经常发现的批处理机包括氧化炉和扩散炉。当问题是确定的且有固定数量的工作到达时,则问题为NP难题;在小问题实例上开发了最佳的动态程序公式并进行了经验测试。对于可能到达工作机会无限的较大问题实例,提出了一种基于模型预测控制(MPC)的在线启发式算法。提议的启发式方法有两个参数:被认为是$ f $的工作家庭数量,以及将来到达的工作量$ L $。对模拟结果的统计分析表明,在到达时间是确定性且连续工作到达的工作族不相关的情况下,基于MPC的启发式方法比基准先行方法的平均周期时间要短得多。当预测的到达时间可能是错误的时,这些观察也成立,表明就预测的到达时间的误差而言,建议的基于MPC的启发式方法与基准一样健壮。当未来工作到达的工作族呈正相关时,无论控制策略如何,通过批处理机的工作的平均周期时间都会大大减少。我们推断,相关性的引入对预见未来事件会更长的政策的改进作用较小。因此,当相关性很高时,基于MPC的启发式方法(考虑到将来发生的事件)可能会比基准性能更差。结果提出了两种提高批处理机性能的方法。首先,我们可以使用具有更好平均性能的启发式方法,这可能会带来更大的计算成本。另一个选择是继续在批处理机上使用简单的预读策略,并将注意力集中在控制上游处理器上,以使批处理机的到达过程在连续到达之间显示相关的作业系列。不论系统参数和批处理程序控制策略如何,这种相关性引入都会显着缩短周期时间。

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