Isabel González, Ismael Sánchez
A methodology for the simulation of out-of-control situations using in-control data is proposed for identifying the alarms that might occur in a multivariate process. The method is based on identifying the independent factors of the variability, and then shifting these factors individually. Shifts called principal alarms are provoked by the most important factors and can be plotted, permitting visualization of the main deviations of the process. Additionally, a resampling procedure is proposed for the estimation of the average run length of a control chart using principal alarms. The methodology is illustrated with a real industrial process application.
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