Robust multivariate control chart based on shrinkage for individual observations

A robust multivariate quality control technique for individual observations is proposed, based on the reweighted shrinkage estimators. simulation study done to check performance and compare method with classical Hotelling approach, alternative minimum covariance determinant estimator. The results show appropriateness of even when dimension or Phase I contamination are high, both independent correlated variables, showing additional advantages about computational efficiency. approach illustrated two real data-set examples from production processes.