About the Project
A fully funded PhD opportunity to participate in the world-leading research undertaken by the EPSRC Doctoral Landscape Award at the University of Sheffield.
Supervised by Prof David Curtis.
The University of Sheffield is one of the leading Russell Group universities in the UK. We carry out cutting-edge research with strong links to industry. When you enrol to do a PhD with us, you will be working with world-leading academics and have access to top of the range facilities. As a PhD student you will have the opportunity to gain skills not only to conduct research, but also to take your career to the next level, whether you want to stay in academia, go into industry or the public sector, or set up your own company. You will have access to a range of training and support services to help you excel in your studies and beyond.
Project Description
Precision grinding is an essential manufacturing process used to shape ultra-hard metals into mission-critical components, such as aerospace turbine blades and power generation shafts. Because these components operate under extreme stress, even microscopic structural damage caused by grinding heat—known as "grinding burn," tempering, or brittle "white layer" formation—can lead to catastrophic failures in service. Currently, manufacturers rely on overly cautious, slow grinding settings or post-process inspection, leading to long cycle times, high energy consumption, and expensive material scrap.
This PhD project will create a "smart" grinding framework that uses thermal modelling and real-time artificial intelligence to dramatically speed up production while guaranteeing zero thermal damage.
The research focuses on two core activities:
- Exploiting Thermal Limits: Rather than grinding cautiously at every stage, the project will build digital models to simulate heat generation and accurately predict the exact burning thresholds of carburised materials. Using this knowledge, the grinding machine can deliberately push cutting speeds past traditional tempering limits during heavy "roughing" cuts to remove metal rapidly. As long as the thin, heat-affected material layer is completely removed during final "finishing" passes, component integrity is preserved while overall process time is reduced by up to 50%.
- Adaptive Monitoring and Data Traceability: Microstructural shifts in hard metals cause grinding power to fluctuate unpredictably, even when machine settings remain constant. To solve this, the researcher will equip industrial grinders with advanced sensor networks (acoustic emission, power meters, thermography, and force sensors). Physics-based machine learning models will analyse these live signals to detect subtle material changes and automatically adjust machine speeds on the fly.
Crucially, every sensor signal will be continuously logged and linked to the component's exact manufacturing stage. This creates a fully traceable "digital thread" and manufacturing passport, giving high-value industries complete digital verification of a part's structural quality throughout its lifecycle.
The student will gain multidisciplinary expertise spanning machine tool operation, modelling approaches, sensor fusion, edge computing, and non-destructive material testing (such as X-ray diffraction and Barkhausen noise). The project directly advances sustainable, zero-defect manufacturing for high-value engineering supply chains.
How to apply
Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.
Please refer to the EPSRC DLA webpage for detailed information about the EPSRC DLA and how to apply.
Applicants must ensure that they use the correct application form linked to the EPSRC DLA webpage and must submit an application for October 2027 entry. The form is unique to the EPSRC DLA. It contains the list of advertised projects from which to select, and three questions specific to the DLA.
The application deadline is 17:00 GMT 13 January 2027.
The majority of our DLA studentships will be allocated to candidates who qualify for Home fee status, in accordance with EPSRC funding regulations which place strict limits on international recruitment.
Funding Notes
The award will fund the full tuition fee and a maintenance stipend at the UKRI rate (currently £21,805 per annum) for 3.5 years, as well as a research grant to support costs associated with the project.