Postgraduate research opportunities Added value of business intelligence for machinery upgrades and modernisation
ApplyKey facts
- Opens: Tuesday 17 January 2023
- Deadline: Friday 31 March 2023
- Number of places: 1
- Duration: 36 months
- Funding: Home fee, Stipend
Overview
This project aims to evaluate the added value of business intelligence for machinery retrofitting, and develop a decision support tool for organisations to make investment decisions through assessing the pros and cons of machinery upgrade.Eligibility
1st class first degree and/or an excellent Masters-level qualification or overseas equivalent in a relevant computer science, management science, operations research, mathematics and statistics, and data science from a recognised academic institution.
Strathclyde Business School is committed to supporting a diverse and inclusive postgraduate research population. We make decisions on entry by assessing the whole person and not relying solely on academic achievements. On that basis, please ensure that your application (via your CV and covering letter) can evidence your resourcefulness, commitment and resilience as demonstrated by broader professional and life experiences. This evidence should be centred on your ability to undertake and complete a PhD and contribute to a positive PhD community.
If English isn't your first language, you'll need an IELTS score of 6.5 or equivalent with no individual element below 5.5.
Your application must include:
- A cover letter presenting your academic path, motivation for doing a PhD and fit with the advertised research project
- An updated curriculum vitae
- Details of two academic referees, including email addresses
- Academic transcripts, which must be certified copies
Project Details
This PhD project aims to develop a decision support tool for organisations’ investment on machinery upgrade and modernisation, through evaluation on the added value of business intelligence versus the current practice.
Specifically, the objectives are as follows:
- To estimate and predict the energy consumptions of legacy machineries based on their usage and operating condition, enabling to extract actional knowledge for operational decisions.
- To develop a predictive maintenance strategy tailored for the legacy machinery and evaluate its added value in reducing machine downtime and improving product quality.
- To evaluate the added value of business intelligence over the current practice in terms of sustainability and productivity.
- To develop a decision support tool for organisations to make investment decisions on equipment upgrade and modernisation.
Funding details
Fully-funded scholarship for 3 years covers all university tuition fees and an annual tax-free stipend for UK students. International students are also eligible for the scholarship, but they would need to find other funding sources to cover the university tuition fee difference between the Home rate and the International rate. Exceptional international candidates may be provided funding for this difference.
Apply
Number of places: 1
There will be a shortlisting and interview process.
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Management Science
Programme: Management Science
Contact us
PhD supervisor:
- Dr Bin Liu: b.liu@strath.ac.uk
- Prof John Quigley: j.quigley@strath.ac.uk