Applications are invited for a research studentship in the field of designing digital twin system modelling of a smart manufacturing factory leading to the award of a PhD degree.
Many parameters, such as movements of input raw materials to machine performance, impact the productivity of a manufacturing factory. Manufacturers are interested in developing tools and techniques based on the digital-twin concept to monitor manufacturing units in real-time and develop smart, proactive strategies to improve the performance. This research project aims to develop intelligent real-time system modelling techniques for industries to assess manufacturing performance. The project focuses on the following research objectives: (i) collecting and analysing real-time factory data, (ii) predicting adaption required in smart manufacturing factory based on real-time information, and (iii) developing a knowledge-based system for providing automatic suggestions to improve manufacturing performance.
The digital twin system modelling tools will be trial tested in a Flexible Manufacturing laboratory environment before studying in an actual manufacturing industry. The research project requires an excellent understanding of manufacturing systems, system engineering principles, data analytics, and predictive modelling techniques. The candidate should have experience in system modelling software such as SimUl8 and using associated advanced programming interfaces.
The researcher joining this project will get skills development and training in the appropriate technical areas. The researcher will be actively encouraged to present the work in leading international conferences and workshops. The researcher should have an appetite for undertaking an enquiring and rigorous approach to research together with a keen intellect and disciplined work habits. The researcher will benefit from collaborating with professors at the University of Edinburgh and the University of Strathclyde through an ongoing EPSRC funded research project.
Successful candidate will be able to conduct lab demonstration classes for additional payment on the top of the stipend.
Academic Qualifications
A first degree (at least a 2:1), ideally in mechanical or systems engineering or operation research with a good fundamental knowledge of data analytics and manufacturing performance analysis, or equivalent Masters degree
English Language requirements
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). other, equivalent qualifications will be accepted. Full details of the University's policy are available online.
Essential attributes
Experience of fundamental knowledge in modelling manufacturing factory network and data analysis
Competent in system modelling simulation software such as SimUl8
Knowledge of programming skills in Python and Matlab
Good written and oral communication skills
Strong motivation and evidence of research skill relevant to the project
Good time management
APPLICATION CHECKLIST
Please quote reference SEBE21006 on your application
• Completed application form (using the given link below)
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (Found on the application process page)
• A personal research statement (This should include (a) a brief description of your relevant experience and skills, (b) an indication of
what you would uniquely bring to the project and (c) a statement of how this project fits with your future direction.)
• Evidence of proficiency in English (if appropriate)
Please apply via this link: https://www.napier.ac.uk/research-and-innovation/research-degrees/application-process
Continue with Facebook
