Rajesh Ganesan

US Patent:

7406396, Jul 29, 2008

Filed:

Nov 8, 2005

Appl. No.:

11/164048

Inventors:

Tapas K Das - Tampa FL, US
Rajesh Ganesan - Tampa FL, US
Arun K Sikder - Tampa FL, US
Ashok Kumar - Tampa FL, US

Assignee:

University of South Florida - Tampa FL

International Classification:

G06F 15/00
G01N 31/00

US Classification:

702181, 702 30

Abstract:

The present invention is an online methodology for end point detection for use in a chemical mechanical planarization process which is both robust and inexpensive while overcoming some of the drawbacks of the existing end point detection approaches currently known in the art. The present invention provides a system and method for identifying a significant event in a chemical mechanical planarization process including the steps of decomposing coefficient of friction data acquired from a chemical mechanical planarization process using wavelet-based multiresolution analysis, and applying a sequential probability ratio test for variance on the decomposed data to identify a significant event in the chemical mechanical planarization process.

US Patent:

7672739, Mar 2, 2010

Filed:

Aug 11, 2006

Appl. No.:

11/464107

Inventors:

Rajesh Ganesan - Centreville VA, US
Tapas K. Das - Tampa FL, US
Kandethody M. Ramachandran - Tampa FL, US

Assignee:

University of South Florida - Tampa FL

International Classification:

G05B 13/02

US Classification:

700 29, 700 42, 700 78

Abstract:

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.

US Patent:

7377170, May 27, 2008

Filed:

Oct 31, 2006

Appl. No.:

11/554716

Inventors:

Rajesh Ganesan - Tampa FL, US
Tapas K. Das - Tampa FL, US
Arun K. Sikder - Tampa FL, US
Ashok Kumar - Tampa FL, US

Assignee:

University of South Florida - Tampa FL

International Classification:

G01N 29/00

US Classification:

73587, 73602

Abstract:

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.

US Patent:

20050223805, Oct 13, 2005

Filed:

Apr 8, 2005

Appl. No.:

10/907633

Inventors:

Rajesh Ganesan - Tampa FL, US
Tapas Das - Tampa FL, US
Arun Sikder - Tampa FL, US
Ashok Kumar - Tampa FL, US

Assignee:

UNIVERSITY OF SOUTH FLORIDA - Tampa FL

International Classification:

G01N029/00

US Classification:

073587000

Abstract:

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.

US Patent:

20100185426, Jul 22, 2010

Filed:

Jan 15, 2010

Appl. No.:

12/688131

Inventors:

Rajesh Ganesan - Centreville VA, US
Poornima Balakrishna - McLean VA, US
Lance Sherry - Fairfax VA, US

International Classification:

G06G 7/70
G08G 5/06
G06F 15/18

US Classification:

703 6, 706 12

Abstract:

A taxi-out time predictor includes an airport simulation processing module, a state vector creation processing module, an actual taxi-out value input processing module and a learning processing module. The airport simulation processing module models airport taxi-out dynamics for a predetermined time period. The actual taxi-out value input processing module collects actual taxi-out measurements from departure aircrafts. The learning processing module includes a reinforcement learning estimation processing module, an update utility processing module and a reward processing module. The reinforcement learning estimation processing module generates a predicted taxi-out time value using the variables in the state vector and an output utility value. The aircraft taxi-out time predictor operates iteratively to predict the taxi-out time.