Monoclonal antibodies (mAbs) are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO) algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies.

The paper addresses the development and implementation of a distributed and hierarchized control system for processes in food industry. More precisely, the wheat grinding and bread production processes that take place at the Mill and bread factory Calafat, Romania, are envisaged. Two solutions based on the DCS/SCADA (Distributed Control System / Supervisory Control and Data Acquisition) architecture are proposed. The first DCS-SCADA structure is a hierarchical monitoring and control system based on digital controllers, data acquisition and computer system. The second structure is a DCS-SCADA hierarchical monitoring and control system based on compact data acquisition and control systems. The configuration and the functionality of the DCS levels are described. Also, the communication interface between the primary control loops and the superior hierarchic levels is presented. The proposed control structures allow the improvement of the overall system currently implemented at the mill and bread factory.