This paper aims to enlarge the family of one-class classification-based control charts, referred to as OC-charts, and extend their\napplications. We propose a new OC-chart using the ????-means data description (KMDD) algorithm, referred to as KM-chart.The\nproposed KM-chart gives the minimum closed spherical boundary around the in-control process data. It measures the distance\nbetween the center of KMDD-based sphere and the new incoming sample to be monitored. Any sample having a distance greater\nthan the radius ofKMDD-based sphere is considered as an out-of-control sample. Phase I and II analysis of KM-chart was evaluated\nthrough a real industrial application. In a comparative study based on the average run length (ARL) criterion, KM-chart was\ncompared with the kernel-distance based control chart, referred to as K-chart, and the ????-nearest neighbor data description-based\ncontrol chart, referred to as KNN-chart. Results revealed that, in terms of ARL, KM-chart performed better than KNN-chart in\ndetecting small shifts in mean vector. Furthermore, the paper provides theMATLAB code for KM-chart, developed by the authors.
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