Model improvement and supersaturation control of crystallization process for the case of agglomeration and breakage

Crystallization process is one of the methods for separating solid-liquid components in the chemical and pharmaceutical industries due to the fact that high quality of crystal products can be obtained. The main specifications of the crystal product are usually given in terms of crystal size distribu...

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Bibliographic Details
Main Author: Zakirah, Mohd Zahari
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/31524/1/Model%20improvement%20and%20supersaturation%20control%20of%20crystallization%20process%20for%20the%20case%20of%20agglomeration%20and%20breakage.wm.pdf
http://umpir.ump.edu.my/id/eprint/31524/
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Summary:Crystallization process is one of the methods for separating solid-liquid components in the chemical and pharmaceutical industries due to the fact that high quality of crystal products can be obtained. The main specifications of the crystal product are usually given in terms of crystal size distribution (CSD). In order to obtain the desired CSD, the supersaturation control can be applied to maintain the concentration at the desired setpoint. Usually current practices point to trial and error method in order to find the setpoint trajectory but it does not guarantee the achievement of the desired CSD. In addition, the crystallization operation usually involves only nucleation and crystal growth phenomena by neglecting the effects of agglomeration and breakage. Therefore, the main objective of this work is to develop a systematic model-based framework for robust supersaturation control in batch cooling crystallization. Through this framework, it is possible to predict the kinetic parameters for representing the crystallization operation, to generate set-point using extended analytical CSD estimator and to perform robustness testing such as set-point tracking, disturbance rejection and uncertainty analysis for achieving robust control. The applications of the model-based framework have been demonstrated through two different case studies. The first case study involves the potassium sulphate crystallization for the case of temperature dependence in nucleation and crystal growth. Meanwhile the effects of agglomeration and breakage is investigated on the sucrose crystallization case study. For both case studies, the necessary kinetic parameters are accurately predicted under open-loop simulation. Based on set-points generated from the extended analytical CSD estimator, the controller is successfully maintained the operation at the required set-point and the desired target CSD is achieved under closed-loop simulation. The developed controller for both case studies are then undergoing set-point tracking and disturbance rejection testing where a good performance has been obtained by judging the ability of the developed controller to adapt the set-point changes and its ability to reject the disturbance introduced to the operation. The robustness of the controller is further evaluated using uncertainty analysis. In this analysis, 6 uncertain input parameters of nucleation and crystal growth are used for potassium sulphate case study and 11 uncertain input parameters of nucleation, crystal growth, agglomeration and breakage are employed for sucrose crystallization. Through uncertainty analysis, it is shown that the proposed controller is performed aggressively to maintain the operation and in the end less variability of the CSD is obtained for both case studies. This shows that supersaturation control has been successfully developed and tested for the case temperature dependence in nucleation and crystal growth as well as the effects of agglomeration and breakage indicating a robust and reliable of the developed controller for this crystallization process.