Abstract
In semiconductor manufacturing industry, run to run (R2R) model based process control (MBPC), which is based on the exponentially weighted moving-average (EWMA) filter, has been widely applied to chemical-mechanical planarization (CMP), chemical vapor deposition (CVD) processes in order to provide the ability to track and compensate for process drifts without a priori assumptions on magnitude or consistency. However, once human interactions and periodic components are added to the R2R process, overall system becomes complex. Therefore a fractional autoregressive integrated moving average (FARIMA) model is proposed to maintain an accurate estimation of how the etching rate changes from R2R or even chamber to chamber (C2C).
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