Control of detergent properties in a spray dryer process

Abstract

This research details the building, implementation and validation of models designed for the control of specific powder detergent properties in a spray dryer process. Findings are reported in two sections; the control of moisture content, particle size distribution (PSD) and bulk density properties; the development of a process model for the online estimation and simulation of the process. The project was completed at Procter & Gamble’s Newcastle Innovation Centre, using a mixed flow spray dryer for the case study. Moisture content can be controlled using a soft sensor to enable estimation of this parameter at a higher sampling frequency than manual measurements of the powder. The proposed empirical model proved to be the most successful approach compared to heat and mass balances. Each model required adjustment of a parameter following the first manual measurement of moisture in a batch run. Control of PSD can be achieved through analysis of droplet size distribution. The dominant influence on the final PSD is the atomization of the slurry, which can be manipulated through changes to the ratio of air and slurry flow to the nozzle. However, numerous sources of variability necessitate continuous amendments to the atomizing air flow rate to maintain the PSD at the required target value. The use of an automatic cascade loop control strategy facilitated manipulation of the air flow to the nozzle, improving control of PSD considerably, halving the response time and reducing variability of mean particle size. Control of bulk density is dependent on an understanding of the key factors that determine the final density of the powder. The density model proposed incorporates statistics for the impact of packing, air entrapment and drying. The model details the limits of the rate of air injection into the slurry, its influence on density control and provides explanations for density changes during the process. viii Separate studies demonstrate the influence of each property on process conditions in each compartment of the mixed flow spray dryer. A model linking these properties to the process conditions has been formulated to provide optimal control strategies for the process. The spray drier involves 3 compartments; a spray chamber, an inner fluid bed and an outer fluid bed. Computational fluid dynamics are used to estimate flow properties and residence times of the chamber and a CSTR model is used to model the fluid beds. The constant drying rate curve (CDRC) and reactor engineering approach (REA) drying models have been implemented and fitted using historical data. A sigmoidal model approach to the CDRC has been included to enable a smoother transition between the constant and falling rate periods. Simulation of the process and online estimations of the powder’s properties were assessed. In each batch, the CDRC model provided the most accurate representation of the process. The CDRC model is recommended for control of the spray drying process and in simulation studies.