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Multivariate statistical process control with artificial contrasts
IIE Transactions, 2007A multivariate control region can be considered to be a pattern that represents the normal operating conditions of a process. Reference data can then be generated and used to learn the difference between this region and random noise. Then multivariate statistical process control can be converted to a supervised learning task.
Wookyeon Hwang +2 more
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Multivariate Statistical Process Control Using LASSO
Journal of the American Statistical Association, 2009This article 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 of being able to select exactly the set of nonzero regression coefficients in multivariate regression modeling, which is especially useful in cases ...
Zou, Changliang, Qiu, Peihua
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Application of Multivariate Statistics to Support Process Control
2005 International Conference on Control and Automation, 2005This paper describes two methods by which multivariate statistics can be exploited to provide benefits to industrial process control. In the first application, the inner structure of a partial least squares model is applied to provide automatic model switching in piecewise linear systems. In the second application, multivariate statistical noise models,
B. Lennox, P. Goulding
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Integrated approach [multivariate statistics process control]
Computing and Control Engineering, 2004We describe about multivariate statistics techniques and exploit within a model-based predictive controller to provide a fully integrated approach to fault detection and isolation, inferential estimation, and model based predictive control . We also discuss intelligent process monitoring.
D. Sandoz, D. Lovett, B. Lennox
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Multivariate Profile Charts for Statistical Process Control
Technometrics, 1994The multivariate profile (MP) chart is a new control chart for simultaneous display of univariate and multivariate statistics. It is designed to analyze and display extended structures of statistical process control data for various cases of grouping, reference distribution, and use of nominal specifications.
Camil Fuchs, Yoav Benjamini
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Statistical process control for multivariate categorical processes
2014Whatever is the business, either manufacturing or service, quality is the most critical aspect, which affects the level of success of the business. The importance of quality cannot be overemphasized. According to its modern definition that quality is inversely proportional to variability, quality improvement is to reduce variability.
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Multivariate Statistical Process Control of a Mineral Processing Industry
1998Multivariate Statitical Process Control procedures are becoming increasingly popular in process industries due to the need for monitoring a large number of process variables simultaneously. Although extensions to classical univariate control charts such as Shewhart, CUSUM and EWMA to multivariate situations are possible, more recently introduced ...
Nihal Yatawara, Jeff Harrison
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Multivariate Statistical Process Control in Chemicals Manufacturing
IFAC Proceedings Volumes, 1997Abstract The close monitoring of the operational performance of process plants and their associated instrumentation and control is of increasing strategic importance. Failures can lead to increased costs, reduced product quality, consistency and production, plant shutdowns and increased environmental impact.
A. Simoglou +4 more
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Monitoring a PVC Batch Process with Multivariate Statistical Process Control Charts
Industrial & Engineering Chemistry Research, 1999Multivariate statistical process control charts (MSPC charts) are developed for the industrial batch production process of poly(vinyl chloride) (PVC). With these MSPC charts different types of abnormal batch behavior were detected on-line. With batch contribution plots, the probable causes of these abnormalities were located. Examples are given for two
Tates, A.A. +4 more
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Multivariate Statistical Process Control of Batch Processes Using PCA and PLS
IFAC Proceedings Volumes, 1994Abstract Multivariate statistical procedures for monitoring the progress of batch processes are developed. The only information needed to exploit the procedures is a historical database of past successful batches. Multi-way Projection to Latent Structures is used to extract the information in the batch set-up data and in the multivariate trajectory ...
John F. MacGregor +2 more
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