Graduation Year

2004

Document Type

Thesis

Degree

M.S.I.E.

Degree Granting Department

Industrial Engineering

Major Professor

Tapas K. Das, Ph.D.

Committee Member

Ashok Kumar, Ph.D.

Committee Member

Jose L. Zayas-Castro, Ph.D.

Committee Member

Qiang Huang, Ph.D.

Keywords

multiresolution, CMP, RbR, dEWMA, denoising

Abstract

Run-by-Run (RbR) control is an online supervisory control strategy designed for the batch manufacturing industry. The objective of RbR control is to minimize process drift, shift and variability between machine runs, thereby reducing costs. The most widely used RbR controllers use the Exponentially Weighted Moving Average (EWMA) filter. However, the linear nature of the EWMA filter makes these RbR controllers inefficient for processes with features at multiple frequencies (also known as multiscale processes). Recent developments in wavelet theory have enhanced the ability to analyze events in multiscale processes. New RbR control strategies have started to emerge that incorporate wavelet analysis. These controllers, developed at the University of South Florida, seem to be robust in dealing with multiscale processes. The objective of this research is to integrate the wavelet based, multiscale analysis approach with the existing double EWMA RbR control strategy for controlling a multiple input multiple output (MIMO) process. The new controller (WRbR controller) is applied on a Chemical Mechanical Planerization process having four inputs and two outputs. A continuous drift and mean shift are introduced in the process, which is then controlled using both the existing double EWMA and the new wavelet based RbR controllers. The results indicate that the wavelet based controller is better in terms of the average square deviation and the standard deviation in the process outputs. Moreover, the observed decrease in the magnitude of the average absolute input deviation indicates a smoother process operation.

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