V. Giner Bosch, P. Castagliola
The relative dispersion of a multivariate process can be measured through the multivariate coefficient of variation (MCV). In this talk, we introduce a one-sided control chart for the MCV-squared of a multivariate normal variable based on the well-known exponentially weighted moving average (EWMA) scheme. The limits of the chart are derived using the properties of the underlying probability distribution, a doubly noncentral F distribution, and some challenging mathematical issues are addressed. The performance of our method in terms of its average run length (ARL) is computed by means of Markov chains. Derivative-free numerical algorithms are applied in order to optimally determine the parameters of the chart. We present numerical experiments showing that our proposal outperforms existing alternatives under different settings.
Keywords: statistical process monitoring, multivariate coefficient of variation, EWMA chart, doubly noncentral F distribution
Scheduled
FCC-2 Reliability and Quality Control
September 5, 2019 12:00 PM
I2L7. Georgina Blanes building