Simultaneous Monitoring of Multivariate Process Mean and Variability in the Presence of Measurement Error With Linearly Increasing Variance Under Additive Covariate Model

In recent years, some researches have been done on simultaneous monitoring of multivariate process mean vector and covariance matrix. however, the effect of measurement error, which exists in many practical applications, on the performance of these control charts is not well studied. in this paper, the effect of measurement error with linearly increasing variance on the performance of elr control chart for simultaneous monitoring of multivariate process mean vector and covariance matrix is investigated. the multiple measurement approach is also extended to reduce this effect. also, the performance of the proposed multiple measurement approach is evaluated in terms of average run length (arl) and standard deviation run length (sdrl). finally, the application of the proposed monitoring method is illustrated by a real data in manufacturing industry.