等离子栅蚀刻的神经网络控制:晶圆到晶圆过程控制的早期步骤

E. Rietman, S. Patel, E. Lory
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引用次数: 7

摘要

研制了一种用于等离子体蚀刻反应器的栅极氧化物厚度控制器。该控制器适用于0.9-/spl mu/m技术。通过监测某些过程,将特征前馈到反向传播方法训练的神经网络中。在每片晶圆的基础上,可以实时预测正确的过蚀刻时间。计算机模拟表明,神经网络在这项任务中相当于人类。该控制器的独特性与以前的1.25-/spl mu/m技术栅极蚀刻工艺的控制器相比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network control of a plasma gate etch: Early steps in wafer-to-wafer process control
A gate oxide thickness controller for a plasma etch reactor has been developed. This controller is for 0.9-/spl mu/m technology. By monitoring certain processes, signatures are fed forward into a neural network trained by the backpropagation method. It is possible to predict in real time the correct over-etch time on a wafer-by-wafer basis. Computer simulations indicate that the neural network is equivalent to humans for this task. The uniqueness of this controller is compared with a previous controller for a 1.25-/spl mu/m technology gate etch process.<>
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