Maximum multivariate exponentially weighted moving average and maximum multivariate cumulative sum control charts for simultaneous monitoring of mean and variability of multivariate multiple linear regression profiles

In some applications, quality of product or performance of a process is described by some functional relationships among some variables known as multivariate linear profile in the literature. In this paper, we propose Max-MEWMA and Max-MCUSUM control charts for simultaneous monitoring of mean vector and covariance matrix in multivariate multiple linear regression profiles in Phase II. The proposed control charts also have the ability to diagnose whether the location or variation of the process is responsible for out-of-control signal. The performance of the proposed control charts is compared with that of the existing method through Monte-Carlo simulations. Finally, the applicability of the proposed control charts is illustrated using a real case of calibration application in the automotive industry. (C) 2017 Sharif University of Technology. All rights reserved.