Adaptive control of photolithography

Authors

  • Oscar D. Crisalle,

    1. Dept. of Chemical and Nuclear Engineering, University of California, Santa Barbra, CA 93106
    Current affiliation:
    1. Department of Chemical Engineering, University of Florida, Gainesville, FL 32611
    Search for more papers by this author
  • Robert A. Soper,

    1. Dept. of Chemical and Nuclear Engineering, University of California, Santa Barbra, CA 93106
    Search for more papers by this author
  • Duncan A. Mellichamp,

    1. Dept. of Chemical and Nuclear Engineering, University of California, Santa Barbra, CA 93106
    Search for more papers by this author
  • Dale E. Seborg

    Corresponding author
    1. Dept. of Chemical and Nuclear Engineering, University of California, Santa Barbra, CA 93106
    • Dept. of Chemical and Nuclear Engineering, University of California, Santa Barbra, CA 93106
    Search for more papers by this author

Abstract

Adaptive control techniques, with their capability for providing satisfactory control even when the process changes with time, are promising candidates for dealing with common problems encountered in photolithography processing such as batch-to-batch variations in resist properties and inconsistencies in resist curing. In this article, an adaptive control strategy for the photolithography process is proposed and evaluated. The design utilizes a reduced-order lithography model, an on-line parameter estimator, and a nonlinear model-inversion controller.

The width of the printed resist lines, a crucial output of photolithography, is controlled by automatically adjusting the exposure energy. In the calculation of the appropriate exposure adjustment, the controller uses both measured critical-dimensions as well as estimated values produced by the process model. The control system is capable of tracking changes in the photolithography process by automatic updating of key model parameters as the process evolves in time. Simulation studies of the closed-loop adaptive control strategy, using the PROLITH simulation package to represent the lithography process, demonstrate the feasibility of this approach.

Ancillary