Design variable-sampling control charts using covariate information

Statistical Process Control (SPC) charts are widely used in manufacturing industry for monitoring the performance of sequential production processes over time. A common practice using a control chart is to first collect samples and take measurements certain quality variables from them at equally-spaced sampling times, then make decisions about process status by based on observed data. In some applications, however, associated with covariates, it should improve an SPC if covariate information can be properly. Intuitively, indicates that under likely have distributional shift soon established relationship between benefit collecting next observation sooner than usual. Motivated this idea, we propose general framework design variable-sampling information. Our proposed self-starting well accommodate stationary short-range serial data correlation. It literature intervals determined Numerical studies show method performs different cases considered.