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In statistical process control, the control chart based on changepoint model does not require prior knowledge about the parameters, making it an attractive technique. So far, changepoint control charts are only developed under normal assumption. But when the underlying distribution
is not normal or unclear, it may not be appropriate. In this paper, we propose a nonparametric changepoint model based on Mann-Whitney
statistic for ongoing Phase II analysis, which has essentially the same computational complexity as the parametric. Its properties under
Phase I situation are investigated, showing this nonparametric model has very similar behavior as the one for normal. This provides us a great guideline for future work in Phase II analysis.