Conveners
Multivariate statistical process control
- Sotiris Bersimis (University of Piraeus, Greece)
Multivariate EWMA control charts were introduced in Lowry et al. in 1992 and became a popular and effective tool for monitoring multivariate data. However, multi-stream data are somehow related to the aforementioned framework. In both cases, correlation between the components respective streams is considered. However, whereas the multivariate EWMA charts deploys a distance (Mahalanobis) in the...
In modern industrial settings, the complexity of quality characteristics necessitates advanced statistical methods using functional data. This work extends the traditional Exponentially Weighted Moving Average (EWMA) control chart to address the statistical process monitoring (SPM) of multivariate functional data, introducing the Adaptive Multivariate Functional EWMA (AMFEWMA). The AMFEWMA...
Statistical process monitoring is of vital importance in various fields such as biosurveillance, data streams, etc. This work presents a non-parametric monitoring process aimed at detecting changes in multidimensional data streams. The non-parametric monitoring process is based on the use of convex hulls for constructing appropriate control charts. Results from applying the proposed method are...