Nonparametric Shewhart-type quality control charts in fuzzy environment

Nonparametric control charts are presented in order to figure out the problem of detecting changes in the process median (or mean), or changes in the variability process where there is limited knowledge regarding the underlying process. When observations are reported imprecise, then it is impossible to use classical nonparametric control charts. This paper is devoted to the problem of constructing nonparametric control charts in presence of fuzzy data and parameters. For this aim, we propose two different methods: distance between fuzzy numbers and credibility measure for ranking fuzzy data, that can be used to construct sign and Wilcoxon signed-rank control charts. Then, this statistical control charts are applied to monitor location and scale parameters of a continuous statistical process. Finally, proposed control charts application is evaluated with numerical examples.