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Run-to-run (RtR) control is an important method for improving process capability. The most common form of RtR controllers are exponentially weighted moving average (EWMA) controllers. The performance of EWMA RtR controllers is affected by the values of the selected tuning parameter. In practice, the tuning parameter usually remains unchanged, resulting in suboptimal performance. In this paper, we propose an adaptive-tuning method for a group and product (G&P) EWMA controller to improve the control performance. The G&P EWMA controller is developed for mixed run processes. We show that the optimum-tuning parameters for the next run of this G&P EWMA controller are obtained online using a window of historical input-output data. The performance improvement due to the proposed method is demonstrated by a simulation example and an industrial application.