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We have 13 Loughborough University, Wolfson School of Mechanical, Electrical and Manufacturing Engineering PhD Projects, Programmes & Scholarships
Loughborough University, Wolfson School of Mechanical, Electrical and Manufacturing Engineering PhD Projects, Programmes & Scholarships
We have 13 Loughborough University, Wolfson School of Mechanical, Electrical and Manufacturing Engineering PhD Projects, Programmes & Scholarships
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Intelligent control of wake aerodynamics for floating offshore wind turbines
For several years, wind energy has been the fastest-growing source of electricity in the UK and EU. Read more
Super-smart textile-based wearable sensing systems for musculoskeletal rehabilitation monitoring
According to the World Health Organisation, over 1 billion of the global population suffer from disabilities. However, access to rehabilitation care has been a global issue due to a lack of resources, including infrastructure and trained professionals. Read more
Improving the efficiency of second generation thin film solar cells
Solar photovoltaics is becoming the most critical source of electricity generation, with over a terawatt installed globally. Although the growth of solar has been extraordinary, it is a young technology with much more scope for improvement. Read more
3D printing tooth: a new ceramic-polymer composite for dental application
This project is supported by two of the most prestigious academic and research organisations in the UK, namely Loughborough University and the Additive Manufacturing Centre of Excellence (AM-COE). Read more
An integrated approach for damage identification in composite materials
Non-destructive inspection based on acoustics is today one of the primary methods for the identification of damage precursors in components and structures. Read more
Modelling slip bands and short crack growth in Ni-based superalloys using discrete crystal plasticity
In metal fatigue, microplastic strain localisation leads to the formation of discrete slip bands, which contribute to the initiation and propagation of short cracks. Read more
Machine learning techniques for 6G wireless networks
Due to spectrum scarcity, efficient use of spectrum such as advanced resource allocation techniques and spatial diversity techniques including massive MIMO has attracted huge interests recently and formed an important part of 5G wireless network design. Read more
Sustainable food production: efficient cleaning processes
Food manufacturing is the largest and one of the most resource intensive sectors in the world. Within this industry, cleaning of food processing equipment is a critical operation to control safety, cross contamination of allergens and maintain food quality. Read more
Improving health in manufacturing
This project is aligned with wider research work which focuses on the manufacturing sector and the physical and mental health and well-being of workers within that sector whose roles have changed and continue to change, at a rapid pace with the introduction of new technology. Read more
Ultraprecision machining in silicon carbide
Silicon carbide is of great importance as a structural ceramic as it is amongst the hardest materials known. Machining silicon carbide parts into the required shape and form for a given application is extremely difficult, yielding unwanted defects. Read more
Predicting failure in crystalline materials using machine learning techniques
Single crystal materials are extensively used in components ranging from the smallest (e.g. micro-lens, MEMS devices) to the largest sizes (e.g. Read more
Next generation hybrid-hybrid machining of critical aerospace parts
The application of laser assisted machining/processing has shown promise in reducing tool wear in the machining of difficult-to-machine aerospace materials, such as, metal matrix composites (MMCs). Read more
Electric field assisted machining
The application of electric-field in materials processing will revolutionise future manufacturing. In comparison with conventional thermo-mechanical processing, it is rapid, consumes less energy, has a lower environmental impact and requires less capital investment. Read more
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