Application of adaptive equipment models to a photolithographic process

Bart J. Bombay; Costas J. Spanos

doi:10.1117/12.56641

1 January 1992 Application of adaptive equipment models to a photolithographic process

Bart J. Bombay, Costas J. Spanos

Proceedings Volume 1594, Process Module Metrology, Control and Clustering; (1992) https://doi.org/10.1117/12.56641
Event: Microelectronic Processing Integration, 1991, San Jose, CA, United States

Abstract

The accurate control of the photolithographic process is critical to the production of VLSI circuits. A control scheme is needed so that deviations from specifications may be compensated by adjustments to the process. Such a control scheme would take advantage of equipment models for the various steps involved in photolithography. Unfortunately, the equipment used for photolithography often changes with time, and is always subject to various disturbances which in turn introduce significant fluctuation in the process performance. In this report, we present an adaptive regression model which will evaluate itself and decide whether it should be refitted to the equipment to better reflect equipment behavior. The model is adaptively modified through recursive estimation based on in-line wafer measurements. Decisions for model changes are based on formal statistical tests which use the principles of the regression control chart [1]. This strategy is being tested on the spin-coat and bake equipment in the Berkeley Microfabrication Laboratory and will soon be extended to the entire lithographic sequence.

Citation Download Citation

Bart J. Bombay and Costas J. Spanos "Application of adaptive equipment models to a photolithographic process", Proc. SPIE 1594, Process Module Metrology, Control and Clustering, (1 January 1992); https://doi.org/10.1117/12.56641

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