multivariate process
Simultaneous Monitoring of Multivariate Process Mean and Variability in the Presence of Measurement Error with Linearly Increasing Variance under Additive Covariate Model (RESEARCH NOTE)
... the process mean and variability are usually developed separately assuming that the other parameter is in ...both process mean and variability should be implemented together because assignable causes can ...
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Multivariate process variability monitoring for general sample design
... There are some multivariate variability measures that have been proposed. For example, Wilks (1932) introduces the covariance determinant, also called generalized variance (GV), | S |, for testing the equality of ...
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A Study of Monitoring Non-normal Multivariate Process Using Support Vector Machine
... K-chart was base on the support vector machine that developed to monitor the multivariate process. The control chart would search the support vector by support vector machine and obtain the kernel distance ...
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Synergistic artificial neural network scheme for monitoring and diagnosis of multivariate process variation in mean shifts
... industries, process variation is known to be a major source of poor ...such, process monitoring and diagnosis is critical towards continuous quality ...(multivariate). Process monitoring ...
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Variable Selection Methods for Multivariate Process Monitoring
... this process according to criterion RX in (5) could be attained by using only six primary ...with process logbook gave clear indications for all known assignable causes present in the ...
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Testing a multivariate process for a unit root using unconditional likelihood
... Unlike the stationary case where least squares and exact maximum likelihood estimates converge to the same normal distribution, the estimates and test statistics converge to different di[r] ...
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A framework for multivariate process monitoring and diagnosis
... Conelusions This paper proposed an integrated MEWMA-ANN scheme towards achieving 'balance monitoring and accurate diagnosis' performances in dealing with bivariate process mean shifts.. [r] ...
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Pattern Recognition of Process Mean Shift using Combined ANN Recognizer
... the process seldom involves several quality characteristics which are usually correlated and require an appropriate technique to monitor these ...the process as it ignores the correlation between the ...
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Short-Run Multivariate Control Charts for Process Mean and Variability
... a multivariate process, when assignable causes are present, they may affect different process parameters: process mean, and/or process variability, and/or process ...a ...
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Detecting Assignable Signals Via Decomposition Of Statistic
... (2002) Multivariate Statistical Process Control with Industrial Applications, ASA-SIAM, ...Implementing Multivariate Process Control Using Hotelling’s T 2 ...for Multivariate Control ...
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Multivariate Statistical Process Control Charts: An Overview
... on process control schemes that are based on a combination of the process outputs and automatic control actions using adaptive ...intelligent process-monitoring and fault-diagnosis environment by ...
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Regression Tensor Modeling of Multivariate Optimization of Process for Applying Metal Coatings
... a multivariate process of sulfur-chromium gives such an opportunity, namely, to identify the most critical parameters and set determined areas of improvement of used and developed techno- logical plants for ...
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Monitoring the variability of petrochemical ZA fertilizer production process based on subgroup observations
... monitoring process variability is also important as monitoring process mean ...controlling multivariate process variability is carried ...monitoring process focus on the sample ...
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Soft Sensor Development for the Measurement of CO2
... In this paper,Gaussian Process Regression is used to develop asoft sensor for measuring the carbon dioxide in the exhaust of a boiler. It is a mathematical model applied in a ladder logic or a computer program to ...
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Study of artificial neural network scheme application in manufacturing industry for monitoring diagnosis bivariate process variation
... a process is under statistical control and to monitor any departures from this ...some process properties over time is tested using certain statistical assumptions about the process (data it ...
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GENETIC VARIATION IN THE ACUTE LETHAL RESPONSE OF FOUR INBRED MOUSE STRAINS TO WHOLE BODY X-IRRADIATION
... On the assumption that the errors from the adjustment process were self-cancelling, a weighted multivariate analysis was executed according to methods described by [r] ...
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Multivariate text mining for process improvement using cross-canonical correlation analysis
... Text analysis is a useful tool to determine what a company and its customers want in order to improve processes and methodologies of analysis. Searches in databases may have a time series component that determines the ...
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A Nonlinear Model with Latent Process for Cognitive Evolution Using Multivariate Longitudinal Data
... latent process, while the main interest of SEM lies in the relation- ship between several latent ...latent process; this gives a description of the evolution of the latent cognitive level for all times in ...
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Modeling a multivariate transaction process
... joint process of price changes, transaction volumes, bid–ask spreads, and intertrade durations on the tick-by-tick time ...change process is discrete whereas the remain- ing three processes are continuous, ...
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QML estimation of a class of multivariate GARCH models without moment conditions on the observed process
... We establish the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator of the parameters of a class of multi- variate GARCH processes. The conditions are mild and coincide with the minimal ...
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