| EPSRC Reference: |
EP/K031430/1 |
| Title: |
Robustness-performance optimisation for automated composites manufacture |
| Principal Investigator: |
Skordos, Dr AA |
| Other Investigators: |
| Iglesias, Dr M |
Long, Professor A |
Schubel, Professor P |
| Ball, Professor FG |
Lesnic, Professor D |
Mehnen, Professor J |
| Cliffe, Professor KA |
Jones, Dr IA |
Potter, Professor K |
| Tretyakov, Professor M |
|
|
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
School of Water, Energy and Environment |
| Organisation: |
Cranfield University |
| Scheme: |
Standard Research |
| Starts: |
11 November 2013 |
Ends: |
10 November 2016 |
Value (£): |
777,199
|
| EPSRC Research Topic Classifications: |
| Manufacturing Machine & Plant |
Materials Processing |
| Non-linear Systems Mathematics |
Numerical Analysis |
| Statistics & Appl. Probability |
|
|
| EPSRC Industrial Sector Classifications: |
|
| Related Grants: |
|
| Panel History: |
| Panel Date | Panel Name | Outcome |
|
19 Feb 2013
|
Maths-Manufacturing Call Prioritisation Panel
|
Announced
|
|
|
Summary on Grant Application Form |
This project focuses on the development of a manufacturing route for composite materials capable of producing complex components in a single process chain based on advancements in the knowledge, measurement and prediction of uncertainty in processing. The methodology proposed uses measurements of the instantaneous state of a component during production, predictive modelling of associated variability and numerical optimisation. These three are integrated in a control loop that allows the process to adapt in real time in order to compensate for deviations from its nominal state due to variability. This manufacturing philosophy accepts the existence of variability in these highly heterogeneous and directional materials and uses it in order to improve the product as the process evolves.
The necessary developments comprise major manufacturing challenges, such as the real time measurement of fibre variability in robotic fibre placement and the processing of composite components involving areas of large thickness. These are accompanied by significant mathematical advancements, such as the numerical solution of coupled non-linear stochastic partial differential equations, the inverse estimation of composite properties and their probability distributions in different directions based on real time measurements and the formulation and solution of a stochastic model of the variability in fibre arrangements. The integration of these developments will be carried out on a single process chain of fibre placement, resin infusion and resin cure; however their applicability is generic in the context of manufacturing involving heterogeneous materials and variability.
The outcome of this work will enable a step change in the capabilities of composite manufacturing technologies to be made, overcoming limitations related to part thickness, component robustness and manufacturability as part of a single process chain, whilst yielding significant developments in mathematics with generic application in the fields of stochastic modelling and inverse problems.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.cranfield.ac.uk |