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(1 - 4 of 4)
Online batch/fed-batch process performance monitoring, quality prediction, and variable-contribution analysis for diagnosis
Title
Online batch/fed-batch process performance monitoring, quality prediction, and variable-contribution analysis for diagnosis
Creator
Undey, C., Ertunc, S., Cinar, A.
Date
2003-10-01
Publisher
AMER CHEMICAL SOC
Description
An integrated online multivariate statistical process monitoring (MSPM), quality prediction, and fault diagnosis framework is developed for...
Show moreAn integrated online multivariate statistical process monitoring (MSPM), quality prediction, and fault diagnosis framework is developed for batch processes. Batch data from I batches, with J process variables measured at K time points generate a three-way array of size I x K x J. Unfolding this three-way array into a two-way matrix of size IK x J by preserving the variable direction is advantageous for developing online MSPM methods because it does not require estimation of future portions of new batches. Two different multiway partial least squares (MPLS) models are developed. The first model (MPLSV) is developed between the data matrix (IK x J) and the local batch time (or an indicator variable) for online MSPM. The second model (MPLSB) is developed between the rearranged data matrix in the batch direction (I x KJ) and the final quality matrix for online prediction of end-of-batch quality. The problem of discontinuity in process variable measurements due to operation switching (or moving to a different phase) that causes problems in alignment and modeling is addressed. Control limits on variable contribution plots are used to improve fault diagnosis capabilities of the MSPM framework. Case studies from a simulated fed-batch penicillin fermentation illustrate the implementation of the methodology.
Endnote format citation for DOI:10.1021/ie0208218
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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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Statistical monitoring of multistage, multiphase batch processes
Title
Statistical monitoring of multistage, multiphase batch processes
Creator
Undey, C., Cinar, A.
Date
2002-10
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Description
The monitoring of intermediate phases of production is as important as monitoring and control of the final stage. Here a framework is proposed...
Show moreThe monitoring of intermediate phases of production is as important as monitoring and control of the final stage. Here a framework is proposed for monitoring overall process performance at the end of each batch.
Endnote format citation
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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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