Prediction-based delay compensation for staged crystallization

Traditionally, the crystallization of active pharmaceutical ingredients (API) and other chemical specialities has been operated in batch or semi-batch mode under strictly regulated recipes. However, batch operations have disadvantages such as lack of batch to batch reproducibility, long processing times, scale up issues, poor controllability and observability. Continuous operation can overcome these drawbacks, although a higher degree of automation and a more in depth process understanding is required for successful continuous API production. Therefore, recent research efforts are directed towards the design of continuous crystallization processes. Multistage mixed suspension mixed product removal (MSMPR) crystallization might be the most convenient route of transition from batch to continuous operation, since current crystallizers in industry are of the stirred tank type. Majority of the work in this area has studied the steady state properties of these systems whereas only a few works deal with the process dynamics and control of these units. In this work, an advanced control scheme for average crystal dimension control in industrial-scale two stage MSMPR crystallizers is proposed and tested in simulation