KEYWORDSaverage run length (ARL); car parts plant; CCC-r control charts; high-quality processes; negative binomial distribution ABSTRACT High-quality industrial processes, characterized by a low fraction of non-conforming items, require paying special attention to the statistical control methods employed since traditional Shewhart's control charts are no longer suitable. In this article, CCC-r charts are considered based on the cumulative count of conforming items inspected until r non-conforming items are observed. However, even though these charts have shown to be useful for high-quality processes, they are characterized by a biased average run length (ARL). In order to help engineers interested in this control methodology to select the best option, a computational study of statistical validation was performed to compare the two most outstanding procedures for the cases r = 2, 3, and 4. The performance was evaluated based on the ARL under control. The application of the CCC-r chart to a real process is shown with data from an automobile parts plant. Finally, analysis and discussion of the results are presented.
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