Counteracting input uncertainty effects of crystallization process in achieving consistent crystal size distribution - Siti Zubaidah, Adnan; Noor Asma Fazli, Abdul Samad (Springer Nature, 2025)
The propagation of input uncertainty in crystallization process can significantly affect the crystal size distribution (CSD). A wide variability in CSD is expected if uncertainty is neglected which may lead to inconsistent product crystal quality and a broad CSD. In this work, the effects of input uncertainty in kinetic models such as nucleation, growth and dissolution parameters as well as seed distribution were evaluated with respect to the desired CSD for a potassium nitrate crystallization process using the Monte Carlo method. Sensitivity analysis using the Standardized Regression Coefficient method was conducted to identify the key parameters influencing CSD. These analyses were performed on a simulated crystallization process using MATLAB software for both unimodal and bimodal seed crystals. Based on Monte Carlo procedure, simulation results from the Proportional-Integral (PI) controller showed significant variation in the final CSD up to 115 µm for the unimodal case and 38 µm for the bimodal case. From the sensitivity analysis of the unimodal case, it was found that 97% of the variation could be attributed to the initial seed CSD, while the growth parameter (g) and nucleation parameter (b) could contribute up to 91% of the variation in the primary and secondary peaks, respectively. In the bimodal case, the growth parameter (g) alone could contribute up to 94% of the variation in both peaks of the final CSD. The PI controller was subsequently retuned which reducing the variation range to 60 µm and 12 µm for the unimodal and bimodal cases respectively indicating successful mitigation of parameter uncertainty.