Statistical process control (SPC) chart is aimed at monitoring a process over time in order to detect any special event that may occur and find assignable causes for it. Controlling both product quality variables and process variables is a complex problem. Multivariate methods permit to treat all the data simultaneously extracting information on the ``directionality" of the process variation. Highlighting the dependence relationships between process variables and product quality variables, we propose the construction of a non-parametric chart, based on Multivariate Additive Partial Least Squares Splines; proper control limits are built by applying the Bootstrap approach.
Non Parametric Control Chart by Multivariate Additive Partial Least Squares via Splines
LOMBARDO, Rosaria;
2008
Abstract
Statistical process control (SPC) chart is aimed at monitoring a process over time in order to detect any special event that may occur and find assignable causes for it. Controlling both product quality variables and process variables is a complex problem. Multivariate methods permit to treat all the data simultaneously extracting information on the ``directionality" of the process variation. Highlighting the dependence relationships between process variables and product quality variables, we propose the construction of a non-parametric chart, based on Multivariate Additive Partial Least Squares Splines; proper control limits are built by applying the Bootstrap approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
