1st class honours/undergraduate degree (essential) and an excellent Masters-level qualification or equivalent (highly desirable), in a closely relevant subject such as computer science, operations research, mathematics and statistics, management science, and industrial engineering, from a recognised academic institution. If English is not your first language, you will also be required to provide evidence such as a recent UKVI recognised English language test (such as IELTS, minimum overall band score of 6.5 with no individual test score below 5.5) or a university degree completed in a recognized English speaking country.
UKRI Studentship Eligibility
The eligibility criteria for UKRI funding has changed for studentships commencing in the 2021/22 academic year. Now, all home and international students are eligible to apply for UKRI funding which will cover the full stipend and tuition fees at the home rate (not the international rate). Under the new criteria, UKRI have stipulated a maximum percentage of international students that can be recruited each year against individual training grants. This will be managed at the institutional level for all EPSRC DTP and ICASE grants. For EPSRC CDT grants, this will be managed by the individual CDT administrative/management team. For ESRC and AHRC studentships the final funding decision will be made by the respective grant holder.
To be classed as a home student, applicants must meet the following criteria:
- Be a UK national (meeting residency requirements), or
- Have settled status, or
- Have pre-settled status (meeting residency requirements), or
- Have indefinite leave to remain or enter.
The residency requirements are based on the Education (Fees and Awards) (England) Regulations 2007 and subsequent amendments. Normally to be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship (with some further constraint regarding residence for education).
If a student does not meet the criteria above, they will be classed as an international student. The international portion of the tuition fee cannot be funded by the UKRI grant and must be covered from other sources. International students are permitted to self-fund the difference between the home and international fee rates.
The researcher is expected to achieve the following objectives:
1. Develop a predictive maintenance tool with knowledge of product quality - Sensors are the machine’s gateway to sense its status and surrounding physical environment. Taking advantage of the sensor measurements, the predictive maintenance model is established to timely intervene the machine. In addition, matching the data from machine sensor and product quality enables to identify the influence of machine degradation on product quality.
2. Establish the evaluation of machine degradation by use of sensor measurements and product quality as the indicators - In traditional studies, the degradation process of the machine is assessed only by the dedicated sensor measurements. However, sensor failure and degradation may pass inaccurate readings to the decision-making algorithms, which leads to suboptimal decisions. Since the product quality somewhat reveals the degradation status of the machine, combination of the product quality and sensor measurements contributes to improving the estimation accuracy of the machine degradation process. A hybrid approach will be developed to evaluate the machine degradation, where machine learning tools will also be employed to enable handling of fast moving and big volumes of data.
3. Design and develop an integrated production and maintenance planning system - The production process and maintenance activities are mutually interactive in such a way that production on various items accelerates (or decelerates) the machine degradation process, which will advance (or postpone) the maintenance activities, while maintenance activities exert impacts on the product quality and thereby the profit. By balancing and compensating the work load and stress for each machine according to their individual health condition, production and machine performance can be maximized. An integrated production and maintenance planning model will be developed aiming to achieve the maximum profit.
Fully-funded scholarship for 3 years which covers all university tuition fees (at UK level) and an annual tax-free stipend. EU/International students are also eligible for the scholarship, but would need to find other funding sources to cover the university tuition fee difference between the Home rate and the International rate. Exceptional EU/International candidates may be provided funding for this difference.
Primary supervisor: Prof Kerem Akartunali
Secondary supervisor: Dr Bin Liu
PhD supervisor: Prof Kerem Akartunali: email@example.com
Dr Bin Liu: firstname.lastname@example.org
Department Administrator: Elaine Monteith: email@example.com
How to apply
How to apply
We require applicants to upload documents in two different places:
- We require you to apply for PhD student using the standard University application system. You can access this here. Candidates applying for this scholarship should ensure that they include the scholarship reference 2354
- We need you to upload your application documentation to this site which will allow us to undertake the required recruitment process for the scholarship. Once you have accessed the folder please upload the following:
- cover letter indicating the candidate's relevant skills/experience and how they can contribute to this research
- transcripts and certificates of all degrees
- proof of English language proficiency if English isn't your first language – IELTS minimum overall band score of 6.5 (no individual test score below 5.5)
- two references (please refer to guidance on references here)
When sending the above documents please use the following file-naming convention: fullname_typeofdocument
Apply now by uploading your documents.