Heteroscedastic latent variable modelling with applications to multivariate statistical process control
نویسندگان
چکیده
منابع مشابه
Multivariate statistical process control using mixture modelling
When performing process monitoring, the classical approach of multivariate statistical process control (MSPC) explicitly assumes the normal operating conditions (NOC) to be distributed normally. If this assumption is not met, usually severe out-of-control situations are missed or incontrol situations can falsely be seen as out-of-control. Combining mixture modelling with MSPC (MM-MSPC) leads to...
متن کاملEconomic Statistical Design of Multivariate T^2 Control Chart with Variable Sample Sizes
Today, quality improvement and cost reduction are key factors for achieving business success, growth and position. One of the primary tools for quality improvement and cost reduction in online activities of statistical process control is control charts. As the need for monitoring several correlated quality characteristics is extensively growing, the use of multivariate control charts become...
متن کاملIntegration of Multivariate Statistical Process Control and Engineering Process Control
Two independent methods for improving quality are engineering process control (EPC) and statistical process control (SPC). The first method tries to minimize variability by handling process variables so as to keep the outputs of the process on target. While the latter method, SPC does the same basic task of minimizing variability by supervising and eradicating the assignable causes of variation...
متن کاملMultivariate statistical process control charts: an overview
In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the...
متن کاملMultivariate Statistical Process Control Using LASSO
This paper develops a new multivariate statistical process control (SPC) methodology based on adapting the LASSO variable selection method to the SPC problem. The LASSO method has the sparsity property that it can select exactly the set of nonzero regression coefficients in multivariate regression modeling, which is especially useful in cases when the number of nonzero coefficients is small. In...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Chemometrics and Intelligent Laboratory Systems
سال: 2006
ISSN: 0169-7439
DOI: 10.1016/j.chemolab.2005.07.002