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Statistical process control of multivariate processes
Control Engineering Practice, 1995Abstract With process computers routinely collecting measurements on large numbers of process variables, multivariate statistical methods for the analysis, monitoring and diagnosis of process operating performance have received increasing attention. Extensions of traditional univariate Shewhart, CUSUM and EWMA control charts to multivariate quality ...
J F Macgregor
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Multivariate statistical process control in chromatography
Chemometrics and Intelligent Laboratory Systems, 1997 Abstract The need for multivariate statistical process control (MSPC) to check the performance of processes is becoming more important as the increasing number of variables that can be measured increases. In this paper Hotelling's T2 statistic based on PCA is used for the development of multivariate control charts.
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Drowsiness Detection Using Multivariate Statistical Process Control
2022Drowsiness at the wheel has been studied for different countries since it is important for road safety and its prevention. Since it is considered a public health problem, solutions must be found to avoid worse scenarios and to identify a low-cost system. Therefore, this work aims to detect the drowsy state, without labeling it manually, considering the
Ana Rita Antunes +2 more
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Integrating multivariate engineering process control and multivariate statistical process control
The International Journal of Advanced Manufacturing Technology, 2005Multivariate engineering process control (MEPC) and multivariate statistical process control (MSPC) are two strategies for quality improvement that have developed independently. MEPC aims to minimize variability by adjusting process variables to keep the process output on target.
Yang, L., Sheu, S.-H.
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Multivariate Statistical Process Control of Electrostatic Separation Processes
2007 IEEE Industry Applications Annual Meeting, 2007Multivariate control charts are commonly used for monitoring processes, the quality of which is determined by two or more correlated output variables. The aim of this paper is to point out the effectiveness of multicriterion control charts for supervising the variability of the outcome of an electrostatic separation process.
Senouci, K. +5 more
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On the Statistical Process Control of Multivariate Autocorrelated Processes
IFAC Proceedings Volumes, 2000Abstract This paper examines how the dynamic information present in a multivariate set of data can be used to improve the performance of a monitoring scheme of the multivariate mean. Optimum performance of such a scheme requires the use of the covariance/correlation matrix of the time-lagged variables.
E. Kaskavelis +3 more
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Multivariate statistics for process control
IEEE Control Systems, 2002Our experience with the application of multivariate statistics to process control began in the late 1980s. Bruce Kowalski, founder of the Center for Process Analytic Chemistry (CPAC), had coined the term chemometrics to describe the application of mathematics and statistics to chemical processes.
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