Statistical process control charts have been widely used for monitoring the quality characteristics of manufacturing processes. Analysis of unnatural patterns is an important aspect of control charting. The occurrence of unnatural patterns implies that a process is influenced by assignable causes, and corrective actions should be taken. In practice, there are many situations in which the simult...


 El propósito de esta investigación es estudiar el proceso producción cartón corrugado en la empresa Productora Cartonera S. A. (PROCARSA). Para ello se evaluó comportamiento las variables calidad resistencia al aplastamiento borde (ECT) y Separación espiga (PAT). Posterior análisis descriptivo, a cada variable le ajustó un diseño factorial, considerando como factores evaluar Operador, Fl...

Multivariate statistical process control charts are often used for process monitoring to detect out-of-control anomalies. However, multivariate control charts based on conventional statistical distance measures, such as the one used in the Hotelling’s T 2 control chart, cannot scale up to large amounts of complex process data, e.g. data with a large number of variables and a high rate of data s...

Amultivariate change point control chart based on data depth (CPDP) is considered for detecting shifts in either the mean vector, the covariance matrix, or both of the process for Phase I. The proposed chart is preferable from a robustness point of view, has attractive detection performance and can be especially useful in Phase I analysis setting where there is limited information about the und...

Monitoring multivariate quality characteristics is very common in production and service environment. Therefore, many control charts have been suggested by authors for monitoring multivariate processes. In another side, profile monitoring is a new approach in the area of statistical process control. In this approach, the quality of a product or a process is characterized by a relation between o...