At CAFE4DM we aim to address the challenges in understanding, creating and scaling up manufacturing processes for formulated products in fast moving consumer goods (home/personal care and food products).
The project combines world leading academic and applied research experience with real industrial relevance. You will work with expert supervisors within Unilever and University of Manchester as the team develops a new modelling approach and the associated materials, measurement and validation to predict the properties of new formulated products associated with fast moving consumer goods (home/personal care and food products).
We have fully funded PhD projects (EU/UK student only) available across a range of subjects relevant for the project. We can offer you a dynamic and supportive environment in which you will carry out independent and original, multidisciplinary research, pushing the boundaries of digital manufacturing.
Computational methods which describe the time dependent changes in microstructures and the effect that this has on the flow properties of complex fluids solution will be examined. These predictive multiphysics tools will be validated using experimental data determined in other parts of the project to assess the mixture morphology during the manufacturing process.
Computational and experimental approaches to enable a detailed understanding of the interactions involved between the components within complex fluid will be studied. X-ray and neutron scattering techniques coupled with 1D and 2D NMR spectroscopic methods will be applied to probe the interactions and structures within the liquid formulations and develop structure property relationships with measured rheological data, for example. This detailed molecular structure information will be used to develop semi-empirical correlative and group contribution models model to predict their physical properties.
Research into the development of in-line measurement tools for product development and manufacturing processes for complex fluids will be undertaken. These methods will be used to design feedback controllers and more advanced model based control systems that utilise process analytical measurements in order to guide design of experiments through intelligent robotic systems. The analytical tools investigated will include electrical resistance and impedance tomography, particle imaging velocimetry, planar laser induced fluorescence and optical coherence tomography.
Research into the barriers associated with behavioural change to introduce new digital tools into manufacturing processes is needed. Our research will specifically focus on the innovation management and behavioural change needed to create a holistic framework for the implementation of technology within the fast moving consumer goods industry.
|Group Contribution methods for non-Newtonian fluids||Details|
|Systems modelling for concentrated crystallizing systems||Details|
|Understanding structure-property relationships in non-Newtonian fluids||Details|