Real-Time Image Processing Based Online Feedback Control System for Cooling Batch Crystallization

Á. Borsos, B. Szilágyi, P.Ş. Agachi, Z.K. Nagy

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

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 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 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 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.
Original languageEnglish
Pages (from-to)511-519
Number of pages9
JournalOrganic Process Research and Development
Volume21
Issue number4
DOIs
Publication statusPublished - 2017

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