A soft sensor for die melt temperature profile prediction of polymer extrusion
Polymeric materials play a major role in production industry and hence advanced process
monitoring is invaluable for improving the product quality and process efficiency. Extrusion is a
fundamental method of processing polymeric materials. An extruder is a machine which
processes materials by conveying it along a screw and forcing it through a die at a certain
pressure. The main function of an extruder is to deliver a homogeneous, well mixed polymer melt
at a specified uniform temperature and pressure. Currently, there are no industrially wellestablished
techniques for online measurement/prediction of the die melt temperature profile and
viscosity of the melt output. Hence, this project aims to first explore the existing melt temperature
and viscosity monitoring techniques used in polymer processing and then propose novel,
industrially-compatible techniques for online monitoring of melt viscosity and melt temperature
profile across the die. Initially, the efficacy of the novel techniques will be explored via simulation
and then will be tested on a medium scale industrial extruder with commonly used polymeric
materials. The aim is that the newly proposed techniques should facilitate advanced process
monitoring and hence to the development of advanced control strategies to optimize the process
energy efficiency and product quality.
Applicants should have or expect to achieve at least a 2.1 honours degree/Masters in Engineering, Physics, Mathematics or Materials Science. Experience in MATLAB, LABVIEW, C++ or other programming languages and modelling/control applications would be preferable.
Funding covers tuition fees and annual maintenance payments of at least the Research Council minimum (currently £14,057) for eligible UK and EU applicants. EU nationals must have lived in the UK for 3 years prior to the start of the programme to be eligible for a full award (fees and stipend). Other EU nationals may be eligible for a fees-only award.