Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Chemical engineering (plants, products), Chemical process engineering
Crystallization control can be improved through real-time monitoring technologies. Here, a workflow is demonstrated on rapid batch cooling crystallization of L-glutamic acid. First, in situ images were generated using video microscopy sensors and analyzed, by employing a single, rapid macro code to extract particle data descriptors. A binning procedure (over time) was performed, where every data point represented the counts of particles within a specific size or shape range per 100 images. This binning method was found more informative in tracking of the populations compared to whole image averages or individual particle datapoints. This study provides a step-by-step guide towards improving mechanistic modeling, control via feedback, automation, and continuous manufacturing for Industry 4.0.
El Arnaout, T. and Cullen, P.J. (2020), In situ Image Processing and Data Binning Strategy for Particle Engineering Applications. Chem. Eng. Technol., 43: 1618-1629. https://doi.org/10.1002/ceat.201900311
EC's Seventh Framework; Science Foundation Ireland