Abstract: Robust control charts for percentiles based on location-scale family of distributions are proposed. In the construction of control charts for percentiles, when the underlying distribution of the quality measurement is unknown, we study the problem of discriminating different possible candidate distributions in the location-scale family of distributions and obtain control charts for percentiles which are insensitive to model mis-specification. Two approaches, which include the random data-driven model selection approach and weighted modeling approach, are used to construct the robust control charts for percentiles to effectively monitor the manufacturing process. The proposed robust control charts are applied to real data sets for the illustration of robustness and usefulness.

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