Closing date: 28 February 2018
Start Date: October 2018
Sponsoring Company: Tata Steel
Academic Supervisor: Dr Xianghua Xie (Computer Science, Swansea University)
Industry 4.0 and Big Data Analysis is receiving more attention in the steel industry to help with improved product quality. Surface inspection systems are used to validate the surface quality, however these then need to be dealt with, possibly resulting in coil rejection. It would be beneficial if processing data could be used to predict the occurrence of certain defects and in time be used to adjust mill processing to reduce the occurrence of defects in real time. Machine learning may also offer some opportunities to improve processes and product consistency.
The project will aim to develop data analytical, machine learning and modelling techniques that can be used on strip steel rolling mills to predict the occurrence of surface defects. This will involve developing data modelling knowledge as well as a sound process knowledge in order to make the connection between data and process. The model would be the basis for other process models for use on other units.
The Athena SWAN Charter recognises work undertaken by institutions to advance gender equality. The College of Engineering is an Athena SWAN bronze award holder and is committed to addressing unequal gender representation.
Candidates should hold an Engineering or Physical Sciences degree with a minimum classification level of 2:1 or equivalent relevant experience. This project is suitable for a candidate with a Mathematical or engineering background with strong data science/computer modelling experience. Candidate will need to develop a good process knowledge for steelmaking and rolling.
We would normally expect the academic and English Language requirements to be met by point of application. For details on the University’s English Language entry requirements, please visit – http://www.swansea.ac.uk/admissions/englishlanguagerequirements/
Our funders require applicants to also meet the following eligibility criteria:
Further information regarding eligibility criteria can be found at: http://www.materials-academy.co.uk/eligibility
The scholarship covers the full cost of UK/EU tuition fees, plus a tax free stipend of £20,000 p.a.