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|Title: ||Real time image processing based on-line feedback control system for cooling batch crystallization|
|Authors: ||Borsos, Akos|
Agachi, Serban P.
Nagy, Zoltan K.
Direct nucleation control
Process analytical technologies
Model free control
|Issue Date: ||2017|
|Publisher: ||© American Chemical Society (ACS)|
|Citation: ||BORSOS, A. ...et al., 2017. Real time image processing based on-line feedback control system for cooling batch crystallization. Organic Process Research & Development, 21(4), pp 511–519|
|Abstract: ||The direct nucleation control (DNC) is a process analytical technique (PAT) based model free feedback control strategy for batch and continuous crystallization processes, which has been successfully applied in numerous cases. The basic principle of DNC is the use of controlled dissolution cycles to control a measurement directly related to the particle number in the system. During the DNC, in the case of cooling crystallization fines are dissolved by repeated heating-cooling loops. In this context, the controlled variable is the (relative) particle number, which is manipulated using a feedback control approach through the temperature. The particle number is traditionally measured with focused beam reflectance measurement (FBRM), however other PAT tools can also be employed in a similar feedback control setup. Often crystallization processes are also monitored by real-time imaging systems. In the current work a novel DNC setup is proposed in which microscopy images are captured and processed by the means of image analysis in real time. The images are used to extract the relative particle number, which is controlled using the DNC framework. The robustness of the new image analysis based direct nucleation control (IA-DNC) is presented via three case studies with materials having different crystallization properties. The IA-DNC approach uses a Particle Vision probe although other in situ or in line imaging systems can also be used in the framework. The systems are monitored with FBRM for comparison purposes. The setup achieved stable, converged control in most cases and is demonstrated that the IA-DNC has several advantages over the classical FBRM based DNC. The IA-DNC can also be used for real time feedback control of crystal shape.|
|Description: ||This document is the Accepted Manuscript version of a Published Work that appeared in final form in Organic Process Research & Development, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://dx.doi.org/10.1021/acs.oprd.6b00242.|
|Sponsor: ||Funding is acknowledged from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013)/ERC grant agreement No. [280106-CrySys].|
|Version: ||Accepted for publication|
|Publisher Link: ||http://dx.doi.org/10.1021/acs.oprd.6b00242|
|Appears in Collections:||Published Articles (Chemical Engineering)|
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