Search results
(1 - 4 of 4)
- 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
Show less
- Title
- Intelligent process monitoring by interfacing knowledge-based systems and multivariate statistical monitoring
- Creator
- Norvilas, A., Negiz, A., Decicco, J., Cinar, A.
- Date
- 2000-08
- Publisher
- ELSEVIER SCI LTD
- Description
-
An intelligent process monitoring and fault diagnosis environment has been developed by interfacing multivariate statistical process...
Show moreAn intelligent process monitoring and fault diagnosis environment has been developed by interfacing multivariate statistical process monitoring (MSPM) techniques and knowledge-based systems (KBS) for monitoring multivariable process operation. The real-time KBS developed in G2 is used with multivariate SPM methods based on canonical variate stare space (CVSS) process models. Fault detection is based on T-2 charts of state variables. Contribution plots in G2 are used for determining the process variables that have contributed to the out-of-control signal indicated by large T-2 values, and G2 Diagnostic Assistant (GDA) is used to diagnose the source causes of abnormal process behavior. The MSPM modules developed in Matlab are linked with G2. This intelligent monitoring and diagnosis system can be used to monitor multivariable processes with autocorrelated, cross-correlated, and collinear data. The structure of the integrated system is described and its performance is illustrated by simulation studies.
Endnote format citation
Show less
- Title
- An intelligent system for multivariate statistical process monitoring and diagnosis
- Creator
- Tatara, E., Cinar, A.
- Date
- 2002-04
- Publisher
- I S A-THE INSTRUMENTATION SYSTEMS AUTOMATION SOC
- Description
-
A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real...
Show moreA knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were prototyped in MATLAB, converted to ANSI C code, and linked with the G2 Standard Interface. The KBS automatically performs all operations of data collection, identification, monitoring, and sensor fault diagnosis with little or no input from the user. Navigation throughout the KBS is via menu buttons on each user-accessible screen. Selected process variables are displayed on charts showing the history of the variables over a period of time. Multivariate statistical tests and contribution plots are also shown graphically. The KBS was evaluated using simulation studies with a polymerization reactor through a nonlinear dynamic model. Both normal operation conditions as well as conditions of process disturbances were observed to evaluate the KBS performance. Specific user-defined disturbances were added to the simulation, and the KBS correctly diagnosed both process and sensor faults when present.
Endnote format citation
Show less
- 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
Show less