Monitoring the covariance matrix of bivariate processes with the DVMAX control charts

• Published in: Applied stochastic models in business and industry Vol. 38; no. 1; pp. 116 - 132
• Main Authors: Machado, Marcela A. G., Lee Ho, Linda, Quinino, Roberto C., Celano, Giovanni
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01-01-2022
• Subjects: average run length; Bivariate analysis; Control charts; Covariance matrix; Inspection; Max D chart; Monitoring; Normal distribution; simulation; Statistical methods; truncated normal distribution; VMAX chart
• ISSN: 1524-1904; 1526-4025
• DOI: 10.1002/asmb.2651

Two versions of Phase II attribute+variable (DVMAX) control charts are investigated for monitoring the covariance matrix ∑ of bivariate processes. Monitoring always starts with an attribute chart employing the Max D control chart and, depending on the outcome, a variable control chart named VMAX chart is run at a second stage to check for process stability. In the first version, denoted as the DVMAX1 chart, two independent samples are used at the two stages of the same inspection; with the second version, denoted as the DVMAX2 chart, the same sample is used at both the first and second stage of the same inspection. This approach, based on the implementation of two types of charts, can be designed to be more advantageous than a single variable control chart in terms of detection speed of a shift in the covariance matrix. In general, we conclude that the DVMAX1 control charts not only shows the best statistical performance but also presents a lower average sampling cost. A numerical example illustrates the implementation of the proposed control charts.