A novel process monitoring solution for composite manufacturing (AMR-01-Kerrigan)

Details

Composite manufacturing has often been described, historically, as a craft industry. Numerous stages of production of a composite part, e.g. vacuum assisted resin transfer moulding (VARTM) and curing, currently do not have a significant process monitoring solution and the process is controlled either by rudimentary sensors, or through a heuristic approach by an experienced, skilled technician. The goal of this research is to identify suitable sensor(s) that enable greater visibility and opportunity for control of a given phase of a composite manufacturing process. The research will take into consideration those manufacturing stages associated with a particular case study part, a composite wind turbine blade, whose manufacture includes processes such as VARTM, curing and machining. This research will include both experimental and numerical simulation to demonstrate the performance of the proposed approach.

The project goals are: 

• To establish the state of the art in sensors suitable for monitoring of composite manufacturing processes, including direct and indirect monitoring approaches.
• Develop encapsulation methods and calibration strategies for in-situ monitoring systems embedded within composite structures.
• Generate an analytical framework to best exploit data derived from a case study manufactured composite component.
• Demonstrate the usefulness of the developed framework for implementation in future such manufacturing processes.

The successful candidate should have the following essential criteria:

• Have a good honours degree (or equivalent) in a relevant field, for example, but not limited to: Materials Science, Mechanical Engineering, Aeronautical Engineering, Physics etc.
• Experience of using sensors to monitor a dynamic response from a system or the ability to demonstrate existing skills can be adapted to such a scenario.
• Technical knowledge of composite materials and manufacturing methods
• Demonstrate experience of using a software programming language, (e.g. Matlab, Python, Java, JavaScript, SQL, C++, etc.) to efficiently and effectively solve an engineering challenge.
• Be self-motivated, able to effectively manage your own time and make informed decisions in the face of a challenge.
• Have good attention to detail and be able to apply this within a meaningful context.
• Have an enduring curiosity and a love of learning.

Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.

Please refer to the EPSRC DTP webpage for detailed information about the EPSRC DTP and how to apply.