Particle processes are both challenging and ubiquitous in industry. The complexity of particulate systems means that it is prohibitively difficult to gain a comprehensive understanding of the particulate mechanics which control a process using solely laboratory experiments. Even though some models are available in the literature which describe particle processes, these tend to be inadequate to meet the requirements of industry. Industry requires robust models which contain the key relevant physics, which are user-friendly and which are focused on delivering the output product specifications given a limited number of measured input parameters.
Despite the significant academic activity in the development of multi-scale, multi-phase modelling approaches, few of the models originating in academia are fully implemented in industrial practice. As a result, the full benefits of model-based development have not been derived. The creation and implementation of a better approach to implementing useful models from academia into industrial practice could therefore lead to significant economic benefits relating to enhanced speed of development, reduced development costs and improved product quality.
This project will create a framework for transferring academic innovations in the modelling of particulate materials into industrial practice with a view to accelerate innovation in formulation development and manufacture across a number of strategically important UK sectors. While this project will generate a methodology which may be fruitfully applied to a wide range of particulate processes, the process of wet granulation will be chosen as an exemplar case study in the first instance. A multi-scale modelling approach is adopted, using the discrete element method to provide particle-level physics and inform the large-scale population balance model. Information will be exchanged between the models  to derive maximum benefit from the two different scales with complementary strengths.
 D. Barrasso, A. Tamrakar, and R. Ramachandran. Chemical Engineering Science, 93, 119, 123:304 – 317, 319 – 329, 500 – 513, 2014, 2015.
The project involves two academic partners, the University of Edinburgh and the University of Sheffield, and six industrial partners: Pfizer, AstraZeneca, Procter and Gamble, Johnson Matthey, Process Systems Enterprise and DEM Solutions. The project is led by the Centre for Process Innovation: the major project funder.