The development of in silico process models for ro.. (IPROCOM)
The development of in silico process models for roll compaction
Start date: Jan 1, 2013,
End date: Dec 31, 2016
"Particulate materials, e.g. pharmaceutical formulations, precious metal, fine chemical, metal & ceramic powders, have been compacted to produce a wide range of particulate products in a number of industrial sectors. The diversity of particulate materials and the complexity of manufacturing processes make it a challenging task in product development and process design for particulate product manufacturing. In particular, their applications in manufacturing high value-added products (such as pharmaceuticals and catalysts) are constrained by a number of scientific and technology hurdles. IPROCOM will address these challenges in a timely manner by bringing together 4 leading European research groups from world-leading universities, 2 national research institutes, and 8 private partners (including 4 SMEs), through a coordinated research and training programme. Our vision is to develop robust in silico process models that can be used to predict the properties of intermediate (ribbons/granules) and final products (tablets/pellets/components) based on the properties of individual particles with identified optimal process conditions and formulations. This will be an innovative and economic tool for product developments, especially for high value-added products. The model will be developed through thorough process understanding and natural synergy of a range of advanced modelling techniques. Our vision will be realised through close collaborations among the partners involved in this truly multidisciplinary IPROCOM consortium, who specialise in complementary areas and possess a broad range of research infrastructures. This will be further enhanced by training a cohort of 12 ESRs and 3 ERs, who will be the next generation technology leaders with the necessary depth and breadth of experience combined with the research and transferable skills to work effectively across disciplinary and sectoral boundaries and competences in applying the in silico tools."
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