Prognostics and predictive analysis incorporating AI and stochastic modelling approach in the railway industry at Glasgow Caledonian University on FindAPhD.com

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Prof B Alkali, Prof Don McGlinchey, Dr O Niculita Applications accepted all year round Self-Funded PhD Students Only

Glasgow United Kingdom Aerospace Engineering Mechanical Engineering

About the Project

Reference number: SCEBE/21SF/004/BA

Aim & Scope

A PhD opportunity in the railway industry. The railway industry is challenged with retrofits of smart condition technology to collect wide range of data information towards performance, availability and reliability improvement. The University has links with NetworkRail, Abellio Scotrail and SNC Lavalin in order to build the research connections

Critical system data capture, extraction as well as analysis is envisaged to support decision making on maintenance. Daily routine task optimisation using data analysis and correlation analysis with real time data collection to determine trend (pattern) of critical or subtle event in the system is an area of interest. The successful PhD candidate will join the Engineering Simulation and Advanced Manufacturing Research Group in the newly launched SMART Technology Research Centre at Glasgow Caledonian University.

In this research study, the candidate is expected to:

Conduct a comprehensive investigation into the use of Virtual Reality, Augmented Reality and digital twin in rail.
Investigate the use multiple criteria decision analysis (MCDA) incorporating AI and stochastic modeling analysis approach and link to dash board system
Conduct risk and reliability data analysis of critical system packages or single units
Conduct literature review and develop a maintenance optimisation model. Then using the model to conduct a simulation projection of what the overall maintenance will be, taking into account relevant factors such as spares, service operations, disruptions, logistics costs and all relevant parameters

The candidate is expected to write a detailed proposal not more than 2000 words clearly stating how any of the points above can be executed in the railway industry.

Candidate need to have an MEng or MSc degree in Engineering Subject or MSc Applied Mathematics with strong quantitative data analytic, computer programming experience.

A bench fee of £4000 is require for attendance of relevant prestigious conferences

How to apply

To apply, please use the relevant link below:

· As a full-time student: https://evision.prod.gcu.tribalsits.com/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=D27ENGXXXFT&code2=0006

· As a part-time student: https://evision.prod.gcu.tribalsits.com/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=D27ENGXXXPT&code2=0006

Funding Notes

Applicants are expected to find external funding sources to cover the tuition fees and living expenses. Alumni and International students new to GCU who are self-funding are eligible for fee discounts.
See more on fees and funding. https://www.gcu.ac.uk/research/postgraduateresearchstudy/feesandfunding/
A bench fee of £4000 is require for attendance of relevant prestigious conferences

References

For further information, please contact:
Director of Studies
Name: Professor Babakalli Alkali
Email:babakalli.alkali@gcu.ac.uk
GCU Research Online URL: https://researchonline.gcu.ac.uk/en/persons/babakalli-alkali
2nd Supervisor Name: Professor Don McGlinchey
Email: D.McGlinchey@gcu.ac.uk
GCU Research Online URL: https://researchonline.gcu.ac.uk/en/persons/don-mcglinchey
3rd Supervisor Name: Dr Octavian Niculita
Email: octavian.niculita@gcu.ac.uk
GCU Research Online URL: https://researchonline.gcu.ac.uk/en/persons/ioan-octavian-niculita