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25 August 1997 Evaluation of model predictive control in run-to-run processing in semiconductor manufacturing
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Abstract
Many steps in the manufacturing of semiconductors offer no opportunity for real-time measurement of the wafer state, necessitating the use of pre- and post-process measurements of the wafer state in a run-to-run control algorithm. The predominant algorithm in the industry is an extended form of SPC using an EWMA filter to adjust a model parameter vector using the available measurements. This paper evaluates the merits of using an optimal discrete controller relying on a discrete-time constrained state-space process model that incorporates feedforward action using the pre-process measurement and feedback using the post-process measurement, accounts for the process statistics using a noise model and optimal filtering theory, and ensures integral action in the controller by estimating unmeasured disturbances. Comparison to the EWMA algorithm are presented using simulations based on actual plant data from a chemical-mechanical polishing application. The polish process is particularly suitable for the application of such a controller because of the natural method the controller provides for incorporating unmeasured disturbances, like pad and slurry changes, in the control action.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James A. Mullins, W. Jarrett Campbell, and Allen D. Stock "Evaluation of model predictive control in run-to-run processing in semiconductor manufacturing", Proc. SPIE 3213, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing III, (25 August 1997); https://doi.org/10.1117/12.284636
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