On the Monitoring of Modern-Day Bivariate Processes

Music City Center 

This study extends recently developed univariate statistical process monitoring (SPM) methods for location and scale to the multivariate setting. Our approach enables the joint monitoring of multiple sequences of critical quality characteristics that exhibit both cross-correlation and autocorrelation. By leveraging copula models, this distribution-free framework addresses the complexities of modern process monitoring, particularly when traditional assumptions such as normality and independence are not met.

Statistical process control

Autocorrelated processes

Multivariate