An Application of the Seasonal Fractional ARIMA Model to the Semiconductor Manufacturing

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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