A Hyper Heuristic Digital Decision Support Methodology for Mixed product Assembly Production
The project will build on work started between the School's of EEECS and MAE in the development of efficient digital manufacturing techniques within the Aerospace transport industry. One key enabler in manufactoring future transportation vehicles is to revolutionize current manufacturing processes by seamless integration of modern computer science and innovative manufacturing approaches. Knowledge based tools incorporating leading edge scheduling and automated techniques can help provide the required step change. The interdisciplinary research team composed of Dr Barry McCollum, Dr Paul McMullan and Dr Yan Jin have already received support from Bombardier and the Northern Ireland Technology Centre in the investigation and development of an intelligent based management information system which is capable of revolutionising the development of components for the aerospace transport industrial sector.
Applicants should have at least an upper second-class honours degree (ideally a first class degree), or a combination of qualifications and/or experience equivalent to that level. Ideally, students should have a BSc or MSc degree in computer science.
The studentship provides full tuition fees and a tax-free stipend of 13,590 per annum for 3.5 years for UK students only.