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Showing 1 to 8 of 8 for “"Multivariate Statistical Process Control"”.
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Contributions to Profile Monitoring and Multivariate Statistical Process Control
… number of cases the quality of a product or process cannot adequately be represented by the distribution of a univariate quality variable or the multivariate distribution of a vector of quality variables. Rather, a series of measurements are taken across some continuum, such as time or space, …
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Nonparametric Multivariate Statistical Process Control Using Principal Component Analysis And Simplicial Depth
Although there has been progress in the area of Multivariate Statistical Process Control (MSPC), there are numerous limitations as well as unanswered questions with the current techniques. MSPC charts plotting Hotelling's T2 require the normality assumption for the joint distribution among the …
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Robust MEWMA-type Control Charts for Monitoring the Covariance Matrix of Multivariate Processes
In multivariate statistical process control it is generally assumed that the process variables follow a multivariate normal distribution with mean vector " and covariance matrix •, but this is rarely satisfied in practice. Some robust control charts have been developed to monitor the mean and …
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Intergration of control chart and pattern recognizer for bivariate quality control
… and diagnosis of mean shifts in manufacturing processes become more challenging when involving two or more correlated variables. Unfortunately, most of the existing multivariate statistical process control schemes are only effective in rapid detection but suffer high false alarm. This is …
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Improvement of cleaning effectiveness through Statistical Process Control in active pharmaceutical ingredient (API) manufacturing
… done to improve the effectiveness of cleaning processes at an active pharmaceutical ingredient (API) manufacturing site that was in the phase of engineering trials and cleaning cycle development. Cleaning cycles executed on the site prior to the project were found to be inconsistent in cleaning …
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Data-rich multivariable detection and diagnosis using eigenspace analysis
… hence the variables are correlated. As a result, multivariate statistical process control is receiving increased attention. This thesis addresses multivariate quality control techniques that are capable of detecting covariance structure change as well as providing information about the real nature …
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Profile Monitoring for Mixed Model Data
… parameter estimators within a general context of multivariate quality control. The goal of Phase I analysis of multivariate quality control data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High …
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APPLICATION OF DATA ANALYTICS AND SPECTROSCOPY ON THE CHEESEMAKING PRODUCTION CHAIN
… were employed to examine the impact of process variables on the food matrix at selected stages of cheesemaking, following the product’s path along its process line. As a first step, the issue of milk coagulation process monitoring through non-intrusive sensors is taken under …