Thesis
A Framework for Understanding and
Controlling Batch Cooling Crystallization
Publications Developing the Framework
Webinar
​
Control of Crystallization,
Webinar hosted by Mettler Toledo
Outcome of my Doctoral Research
A Framework for Understanding and Controlling
Batch Cooling Crystallization
Motivated by the difficulty of applying prevailing design strategies to establish control of crystallization, my research advisors (Professors Grover, Kawajiri, and Rousseau) and I developed a new framework.
This framework, which we have labeled the Mass-Count Framework, was designed to facilitate an understanding of batch cooling crystallization dynamics and enable control of crystal size. But we believe that the framework can also find extended applications.
​
The work was captured in a series of publications and in my Thesis. These are provided below along with a webinar and code for performing data-driven modeling and dynamic programming (real data included).
Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization
​
Taking the human out of the loop: application of an algorithmic solution to control design
Mass-Count Plots for
Crystal Size Control
​
Introduction of the framework and application to a salt crystallization system relevant to nuclear waste separation
Using Mass-Count Plots for Control of Paracetamol Crystallization
​
Application of the framework to control a crystallization system relevant to the pharmaceutical industry
Published Code
​
Data-Driven Modeling and Dynamic Programming