(499c) Application of ICAS-PAT On Design of Process Monitoring and Control System for a Batch Cooling Crystallization Process through Hybrid Multiscale Model-Based Analysis
AIChE Annual Meeting
Thursday, November 12, 2009 - 9:20am to 9:45am
A well designed process monitoring & control systems insures that the critical process variables are measured and maintained within the design space and therefore predefined end product quality can be achieved precisely and consistently. Design of process monitoring and control system involves the identification of the critical quality parameters, selection of economical & reliable data measurement methods/tools and implementation with the efficient control systems. Singh et al., (2009) proposed the use of a systematic model and knowledge based methodology to design/validate the PAT systems (process monitoring & analysis systems) and implemented this methodology into a systematic computer aided framework to develop a software (ICAS-PAT) to make the PAT design procedure simpler, better and faster. The software ICAS-PAT is now extended to incorporate the detailed control algorithm, needed to design/validate the product quality through implementation of efficient and advanced control systems. In the control algorithm, options for steady state and dynamic analysis are implemented. The steady state analysis is developed in order to identify candidate operational scenario and analyzed using steady state sensitivity analysis. This analysis is then transferred to corresponding dynamic model to assess controllability performances using steady state and dynamic relative gain array and interaction between controlled and manipulated variable. The extended version of ICAS-PAT is therefore now capable to provide the product recipe that can be directly use in the manufacturing floor to produce the product with desired quality. The main feature of new software is the design of PAT systems. However, some additional features are also developed to provide the options to open and analyze the solved examples, to identify the different applications of the monitoring techniques/tools, to generate the possible alternatives of the PAT systems, to generate a report in MS-Word and to generate closed/open loop process flow-diagrams (indicating also the monitoring and control schemes).
The objective of this presentation is two-fold, first to highlight the extension of the framework and the corresponding software (ICAS-PAT) and then to demonstrate their application through a batch cooling crystallization process. The extended ICAS-PAT is integrated with two supporting tools: an extended knowledge base and a generic model library needed to provide the necessary knowledge/data for design of process monitoring and control systems. The extended knowledge base consists of two sections. The first section of the knowledge base summarizes the necessary process knowledge (type of processes, corresponding process points, process variables and actuators) while the second section of the knowledge base consist of the knowledge on measurement methods and tools (type of variables, available monitoring techniques and tools with specifications such as accuracy, precision, operating range, response time, resolution, cost etc.). The model library contains a set of mathematical models for different types of unit processes, sensors and controllers.
The application of ICAS-PAT and the new framework will be illustrated through a batch crystallization process, a most common unit operation used when isolating the final product. Usually the quality specification for crystalline substances is the desired crystal size distribution (CSD). The intriguing problem here is to determine how to monitor & control the crystallization operation during a batch run such that a desired CSD is obtained at the end of the batch. As needed for design & validate the process monitoring & control system, a generic hybrid multiscale batch crystallization process model has been developed and included in model library.
Reference: Singh, R., Gernaey, K. V., Gani, R., (2009). Model-based computer-aided framework for design of process monitoring and analysis systems. Computers & Chemical Engineering, 33, 22-42
PAT: Process Analytical Technology
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