No abstract

Processes involving particles, are known to exhibit extremely unpredictable behaviour, mainly due to the mesoscopic nature of granular media. Understanding particulate processes, not only for intellectual satisfaction, but also for process design and operation, basically requires a systems approach in modelling. Because they combine simplicity and flexibility, the stochastic models based on the Markov chain theory are very valuable mathematical tools to this respect. However, they are still largely ignored by the whole core of chemical engineering researchers. This motivates the existence of this review paper, in which we examine the three traditional issues: mixing and transport, separation and transformation.

While it would provide many advantages from many aspects, the application of continuous mixing processes to the pharmaceutical field is still in its infancy. In this paper we report results concerning the continuous mixing of nine ingredients (including three actives) that constitute a current drug. We examine these results in the light of different pharmaceutical process constraints, such as mixture quality control, time-stability of this quality, sensitivity of the process to perturbations. The apparatus is a pilot plant Gericke GCM 500 continuous mixer with three loss-in-weight feeders. A specific experimental protocol is developed to determine the homogeneity of the mixtures at the outlet of the mixer. The homogeneity of the mixtures is examined through industrial standards that would allow the product to be released on the market. The steady-state operation is first reported on, and it is demonstrated that a very acceptable mixture can be produced under certain conditions, with excellent time stability. The response of the mixer to filling sequences of two critical feeders is also quantified in terms of mixture homogeneity. It is found that it may be preferable to stop the process during these periods.