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Advanced process control of a CVD tungsten reactor

机译:CVD钨反应器的高级过程控制

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An advanced multivariable in-line process control system, which combines traditional statistical process control (SPC) with feedback control, has been applied to the CVD tungsten process on an Applied Materials reactor. The goal of the model-based controller is to compensate for shifts in the process and maintain the wafer-state responses on target. The controller employs measurements made on test wafers to track the process behavior. This is accomplished by using model-based SPC, which compares the measurements with predictions obtained from process models. The process models relate the equipment settings to the wafer-state responses of interest. For CVD tungsten, a physically-based modeling approach was employed based on the reaction rate for the H/sub 2/ reduction of WF/sub 6/. The Arrhenius relationship for the kinetic model was linearized so that empirical modeling techniques could be applied. Statistically valid models were derived for deposition rate, film stress, and bulk resistivity using stepwise least-squares regression. On detecting a statistically significant shift in the process, the controller calculates adjustments to the settings to bring the process responses back on target. To achieve this, two additional test wafers are processed at slightly different settings than the current recipe. This local experiment allows the models to be updated to reflect the current process state. The model updates are expressed as multiplicative or additive changes in the process inputs and a change in the model constant. This approach for adaptive control also provides a diagnostic capability regarding the cause of the process shift. The adapted models are used by an optimizer to compute new settings to bring the responses back to target. The optimizer is capable of incrementally entering controllables into the strategy, reflecting the degree to which the engineer desires to manipulate each setting. The capability of the controller to compensate for induced shifts in the CVD tungsten process is demonstrated. Targets for film bulk resistivity and deposition rate were maintained while satisfying constraints on film stress and WF/sub 6/ conversion efficiency. The ability of the controller to update process models during routine operation is also investigated. The tuned process models better predict the process behavior over time compared to the untuned models and lead to improved process capability.
机译:先进的多变量在线过程控制系统将传统的统计过程控制(SPC)与反馈控制相结合,已应用于应用材料反应堆上的CVD钨工艺。基于模型的控制器的目标是补偿过程中的偏移并保持目标上的晶圆状态响应。控制器采用在测试晶圆上进行的测量来跟踪工艺行为。这可以通过使用基于模型的SPC来完成,该模型将测量结果与从过程模型获得的预测进行比较。工艺模型将设备设置与感兴趣的晶圆状态响应相关联。对于CVD钨,根据H / sub 2 / WF / sub 6 /的还原反应速率,采用基于物理的建模方法。动力学模型的Arrhenius关系被线性化,因此可以应用经验建模技术。使用逐步最小二乘回归法得出了统计上有效的沉积速率,膜应力和体电阻率模型。在检测到过程中发生统计上显着的变化时,控制器会计算对设置的调整,以使过程响应恢复到目标状态。为了实现这一点,在与当前配方略有不同的设置下处理了两个额外的测试晶圆。该本地实验允许更新模型以反映当前的过程状态。模型更新表示为过程输入中的乘性或加性变化以及模型常数的变化。这种用于自适应控制的方法还提供了有关过程偏移原因的诊断功能。优化器使用调整后的模型来计算新设置,以将响应带回到目标。优化器能够将控制标签逐步输入到策略中,以反映工程师希望操纵每个设置的程度。证明了控制器补偿CVD钨工艺中感应位移的能力。维持薄膜体电阻率和沉积速率的目标,同时满足对薄膜应力和WF / sub 6 /转换效率的限制。还研究了控制器在常规操作期间更新过程模型的能力。与未调整的模型相比,已调整的过程模型可以更好地预测一段时间内的过程行为,并提高过程能力。

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