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Showing 1 to 13 of 13 for “"Multivariate quality control"”.
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A theoretical framework for multivariate quality control
Restriction data tranferred 2014-07-01T11:15:55-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission
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The Minimax control chart for multivariate quality control
A new multicharacteristic control chart designed to detect shifts in the mean of a multivariate process is proposed. It is assumed that the correlation matrix is known and that the distribution of the data is multivariate normal. The new chart is based on the minimum standardized sample mean …
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A Multivariate Quality Control Approach for Automated Manufacturing Systems
… environment, effective and practical statistical quality control approaches are essential. A successful process control approach needs to provide on line real time monitoring of quality related characteristics.</p> <p>No longer acceptable is an approach that analyzes quality related data only …
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A Performance Analysis of the Minimax Multivariate Quality Control Chart
A performance analysis of three different Minimax control charts is performed with respect to their Chi-Square control chart counterparts under several different conditions. A unique control chart must be constructed for each process described by a unique combination of quality characteristic mean …
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The application of a single control chart for dependent variables in multivariate quality control
Most control charts monitor only one quality characteristic. There are, however, many manufactured products for which good quality requires meeting specifications in more than one physical characteristic. Typical practice when dealing with multiple quality characteristics is to take a separate …
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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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Simultaneous process control of several independent quality variables
A method for multivariate quality control with the dual objectives of providing a true level of sampling error probabilities for the joint control of several quality variables while also giving problem diagnoses for the quality variables individually. The method is comprised of an afine …
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Statistical process control with special reference to multivariable processes and short runs
The quest for control and the subsequent pursuit of continuous quality improvement in the manufacturing sector, due to increasingly keen competition, has stimulated interest in statistical process control (SPC). Whilst traditional SPC techniques are well suited to the mass production industries, …
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Control chart procedures based on cumulative gauging scores
Control charts based on cumulative gauging scores rely on gauge scoring systems used for transforming actual observations into integer gauging scores. In some cases, the gauging scores are easy to obtain by using a mechanical device such as in the go-no-go inspection process. Thus, accurate …
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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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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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Contributions to quality improvement methodologies and computer experiments
… methodologies for five problem areas in modern quality improvement and computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate quality control, model selection for split plot experiments, and construction of minimax designs. Selective assembly has …