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Virtual Metrology and Run-to-Run Control in Semiconductor Manufacturing

机译：半导体制造中的虚拟计量和运行控制

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摘要

Virtual Metrology (VM) generally refers to a model based prediction of some process outcome in place of, or in the absence of, an actual physical measurement of that outcome. The underlying models are learned from histories of the actual physical outcomes and predictors that may include process trace data, tool consumable status, and incoming work characteristics. If the models are sufficiently accurate predictors of process outcomes, VM applications present the opportunity to reduce the number of physical measurements made to monitor a process, while maintaining or even improving quality control. Such applications are especially attractive for highly complex, capital intensive semiconductor manufacturing lines, in which measurements monitoring processes may add significant processing time and cost. In this paper, we propose a model for metrology variable prediction with tensor input process variables by directly operating on the tensor. Experimental results demonstrate the good performance of this model compared to others that are widely discussed in the literature of VM and deal with only one-dimensional inputs. We also propose three VM embedded run-to-run (R2R) control schemes that can facilitate feedback control based on the actual and virtual metrology values. We demonstrate the ability of the proposed control schemes to effectively reduce the process variation based on experiment results.
机译：虚拟计量学（VM）通常是指基于模型的某些过程结果的预测，代替或没有该结果的实际物理测量。基本模型是从实际物理结果和预测变量的历史中获悉的，这些预测变量可能包括过程跟踪数据，工具消耗状态以及进来的工作特征。如果模型足够准确地预测过程结果，则VM应用程序将提供机会减少为监视过程而进行的物理测量，同时保持甚至改善质量控制。这样的应用对于高度复杂，资本密集型的​​半导体生产线特别有吸引力，在这些生产线中，测量监视过程可能会增加大量的处理时间和成本。在本文中，我们通过直接在张量上操作，提出了一个具有张量输入过程变量的计量变量预测模型。与在VM文献中广泛讨论且仅处理一维输入的其他模型相比，实验结果证明了该模型的良好性能。我们还提出了三种VM嵌入式运行到运行（R2R）控制方案，这些方案可以促进基于实际和虚拟度量值的反馈控制。我们根据实验结果证明了所提出的控制方案有效减少过程变化的能力。

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