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Integration of multivariate SPM and FDD by parity space technique for a food pasteurization process
Title
Integration of multivariate SPM and FDD by parity space technique for a food pasteurization process
Creator
Kosebalaban, F., Cinar, A.
Date
2001-03-15
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Description
Multivariate statistical process monitoring (MSPM), contribution plots, and parity space fault diagnosis (FD) techniques are used to detect...
Show moreMultivariate statistical process monitoring (MSPM), contribution plots, and parity space fault diagnosis (FD) techniques are used to detect abnormal operation of dynamic processes and diagnose sensor and actuator faults. The methods are illustrated by monitoring the critical control points (CCP) and diagnosing causes of abnormal operation of a pilot pasteurization plant. An empirical model of the process is developed by using subspace state space system identification methods and normal process data. The process data collected under the influence of different magnitude and duration of faults in sensors and actuators are used to validate the MSPM and FD techniques. T-2 and squared prediction error (SPEN) charts are used as MSPM charts. A parity space technique for dynamic stochastic systems and dynamic trends in contribution plots of T-2 and SPEN statistics are used for FD. The detection and FD by these techniques show significant improvements over univariate methods.
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Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations
Title
Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations
Creator
Undey, C., Tatara, E., Cinar, A.
Date
2004-02-19
Publisher
ELSEVIER SCIENCE BV
Description
Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality...
Show moreSupervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for online real-time process monitoring and the multivariate monitoring charts are presented. This online process monitoring technique is also extended to include predictions of end-of-batch quality measurements during the progress of a batch run. Process monitoring, quality estimation and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.
Endnote format citation for DOI:10.1016/j.jbiotec.2003.10.004
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Real-time batch process supervision by integrated knowledge-based systems and multivariate statistical methods
Title
Real-time batch process supervision by integrated knowledge-based systems and multivariate statistical methods
Creator
Undey, C., Tatara, E., Cinar, A.
Date
2003-08
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Description
Real-time supervision of batch operations during the progress of a batch run offers many advantages over end-of-batch quality control. Process...
Show moreReal-time supervision of batch operations during the progress of a batch run offers many advantages over end-of-batch quality control. Process monitoring, quality estimation, and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling and fault diagnosis. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide a powerful modeling, monitoring, and supervision framework. Online process monitoring techniques are developed and extended to include predictions of end-of-batch quality measurements during the progress of a batch run. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.
Endnote format citation for DOI:10.1016/j.engappai.2003.09.003
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Batch process monitoring and its application to polymerization systems
Title
Batch process monitoring and its application to polymerization systems
Creator
Undey, C., Ertunc, S., Tatara, E., Teymour, F., Cinar, A.
Date
2004-01
Publisher
WILEY-V C H VERLAG GMBH
Description
Slight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization...
Show moreSlight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization reactors may have a strong influence on reaction mechanism and impact final product quality. Online process monitoring, fault detection, fault diagnosis, and product quality prediction in real-time ensure safe reactor operation and warn operators about excursions from normal operation that may lead to deterioration in product properties. Multivariate statistical process monitoring and quality prediction using multiway principal components analysis and multiway partial least squares have been successful in detecting abnormalities in process operation and product quality. When abnormal process operation is detected, fault diagnosis tools are used to determine the source cause of the deviation. Illustrative case studies are presented via simulated polyvinyl acetate polymerization.
Endnote format citation for DOI:10.1002/masy.200450210
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