Results 241 to 250 of about 15,402,643 (297)
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Multivariate statistical monitoring of process operating performance
The Canadian Journal of Chemical Engineering, 1991AbstractProcess computers routinely collect hundreds to thousands of pieces of data from a multitude of plant sensors every few seconds. This has caused a “data overload” and due to the lack of appropriate analyses very little is currently being done to utilize this wealth of information.
James V. Kresta +2 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 Monitoring Based on Statistics Pattern Analysis
Industrial & Engineering Chemistry Research, 2010In this work, a new multivariate method to monitor continuous processes is developed based on the statistics pattern analysis (SPA) framework. The SPA framework was proposed recently to address some challenges associated with batch process monitoring, such as unsynchronized batch trajectories and multimodal distribution.
Jin Wang, Q. Peter He
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Multivariate statistical process monitoring based on blind source analysis
SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2004In this paper, a new multivariate statistical process control (MSPC) method is presented based upon blind source analysis and wavelet transform. Blind source analysis based on ICA (independent component analysis) is used to compress the information in the data into low-dimensional spaces.
Guo-jin Chen, Jun Liang, Ji-Xin Qian
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Multivariate Statistical Monitoring of Wine Ageing Processes
2010Abstract The flavor pattern is a key quality feature in the wine industry. Being the result of a complex interplay of different classes of volatile compounds, it presents an important evolution during the final and longer phase of the wine production process: the ageing period.
Ana C. Pereira +3 more
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Industrial use of multivariate statistical analysis for process monitoring and control
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2003Multivariate statistical analysis has come of age over the last decade. Dofasco, a leading North American provider of Solutions in Steel/spl trade/ and Tembec, a multinational, integrated forest products company have applied this technology in many industrial applications. The intent of the paper is to give an introduction to the application of on-line
Marc Champagne, Michael Dudzic
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Statistical process monitoring and disturbance diagnosis in multivariable continuous processes
AIChE Journal, 1996AbstractDetecting out‐of‐control status and diagnosing disturbances leading to the abnormal process operation early are crucial in minimizing product quality variations. Multivariate statistical techniques are used to develop detection methodology for abnormal process behavior and diagnosis of disturbances causing poor process performance.
Anne Raich, Ali Çinar
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The application of multivariate statistical process monitoring in non-industrial processes
Quality Technology & Quantitative Management, 2016AbstractStatistical process monitoring (SPM) techniques have been widely used in industry for many decades in order to assess the process stability, as well as the final product quality. Interestingly, SPM techniques have gained popularity in many non-industrial fields providing even more opportunities for research.
Sotiris Bersimis +2 more
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Multivariate Statistical Monitoring of a High‐Pressure Polymerization Process
Polymer Reaction Engineering, 2003The high pressure LDPE (low density polyethylene) industrial process operates under supercritical conditions, and so it is necessary to monitor its performance to prevent abnormal situations.
V. Kumar +4 more
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Multivariate statistical process monitoring of batch‐to‐batch startups
AIChE Journal, 2015In batch processes, multivariate statistical process monitoring (MSPM) plays an important role for ensuring process safety. However, despite many methods proposed, few of them can be applied to batch‐to‐batch startups. The reason is that, during the startup stage, process data are usually nonstationary and nonidentically distributed from batch to batch.
Zhengbing Yan, Bi‐Ling Huang, Yuan Yao
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