公开(公告)号：US07672739B2

公开(公告)日：2010-03-02

申请号：US11464107

申请日：2006-08-11

申请人： Rajesh Ganesan ,  Tapas K. Das ,  Kandethody M. Ramachandran

发明人： Rajesh Ganesan ,  Tapas K. Das ,  Kandethody M. Ramachandran

IPC分类号： G05B13/02

CPC分类号： G05B13/048 ,  G05B11/42

摘要： A new multiresolution analysis (wavelet) assisted reinforcement learning (RL) based control strategy that can effectively deal with both multiscale disturbances in processes and the lack of process models. The application of wavelet aided RL based controller represents a paradigm shift in the control of large scale stochastic dynamic systems of which the control problem is a subset. The control strategy is termed a WRL-RbR controller. The WRL-RbR controller is tested on a multiple-input-multiple-output (MIMO) Chemical Mechanical Planarization (CMP) process of wafer fabrication for which process model is available. Results show that the RL controller outperforms EWMA based controllers for low autocorrelation. The new controller also performs quite well for strongly autocorrelated processes for which the EWMA controllers are known to fail. Convergence analysis of the new breed of WRL-RbR controller is presented. Further enhancement of the controller to deal with model free processes and for inputs coming from spatially distributed environments are also addressed.

摘要翻译： 一种新的多分辨率分析（小波）辅助强化学习（RL）控制策略，可以有效地处理过程中的多尺度扰动和缺乏过程模型。 基于小波辅助RL的控制器的应用代表了控制问题是一个子集的大规模随机动态系统的控制范式转移。 控制策略称为WRL-RbR控制器。 WRL-RbR控制器在晶圆制造的多输入多输出（MIMO）化学机械平面化（CMP））工艺中进行测试，该工艺模型可用。 结果表明，RL控制器优于基于EWMA的控制器，用于低自相关。 新的控制器对于已知EWMA控制器故障的强自相关过程也表现相当好。 介绍了新一代WRL-RbR控制器的收敛分析。 还讨论了进一步增强控制器来处理无模式的进程和来自空间分布式环境的输入。

公开(公告)号：US07377170B2

公开(公告)日：2008-05-27

申请号：US11554716

申请日：2006-10-31

申请人： Rajesh Ganesan ,  Tapas K. Das ,  Arun K. Sikder ,  Ashok Kumar

发明人： Rajesh Ganesan ,  Tapas K. Das ,  Arun K. Sikder ,  Ashok Kumar

IPC分类号： G01N29/00

CPC分类号： G01N29/4427 ,  B24B37/005 ,  B24B49/003 ,  G01N29/043 ,  G01N29/14 ,  G01N29/42 ,  G01N29/4445 ,  G01N29/46 ,  G01N2291/0231 ,  G01N2291/2697

摘要： The present invention presents a novel application of a wavelet-based multiscale method in a nanomachining process chemical mechanical planarization (CMP) of wafer fabrication. The invention involves identification of delamination defects of low-k dielectric layers by analyzing the nonstationary acoustic emission (AE) signal collected during copper damascene (Cu-low k) CMP processes. An offline strategy and a moving window-based strategy for online implementation of the wavelet monitoring approach are developed.

摘要翻译： 本发明提出了在晶片制造的纳米加工过程化学机械平面化（CMP）中基于小波的多尺度方法的新颖应用。 本发明涉及通过分析在铜镶嵌（Cu-low k）CMP工艺中收集的非平稳声发射（AE）信号来识别低k电介质层的分层缺陷。 开发了用于在线实现小波监测方法的离线策略和基于窗口的移动策略。

公开(公告)号：US07617523B2

公开(公告)日：2009-11-10

申请号：US11256849

申请日：2005-10-21

申请人： Tapas K. Das ,  Nitin Sharma ,  Jingxue Shen

发明人： Tapas K. Das ,  Nitin Sharma ,  Jingxue Shen

IPC分类号： H04L29/06

CPC分类号： G06F21/41

摘要： Authentication mechanisms for accessing one or more applications by a user by using collaborative agents for automating authentication to the one or more applications. The use of collaborative agents obviates a need for the user to remember fortified authentication credentials for each application.

摘要翻译： 用于通过使用协作代理来访问一个或多个应用程序以用于对一个或多个应用进行自动认证的认证机制。 协作代理的使用避免了用户记住每个应用程序的强化身份验证凭据的需要。