New FEMM Hub Studentship Announced In Advanced Manufacturing of Copper Conductors
We are pleased to announce the latest FEMM Hub PhD based at the University of Sheffield.
PhD title: Advanced Manufacturing of Copper Conductors for Electric Machines
About the Project
Supervisory team:
Prof Hassan Ghadbeigi (Mechanical Engineering)
Prof Geraint Jewell (Electrical and Electronic Engineering)
Overview
Applications are invited for a fully funded PhD position (at UK student rates) focusing on the development and optimization of manufacturing processes for copper conductors used in next-generation electrical machines. This project sits at the intersection of advanced manufacturing, materials science, and data-driven process optimization.
Project Description
Electrical machines are crucial components in various applications, from electric vehicles to industrial drives. The efficiency and performance of these motors heavily depend on the thermal management of their copper windings. This PhD project aims to:
Develop novel forming technologies for manufacturing rectangular section copper conductors with a degree of precision beyond current industry practice
Create adaptive optimization frameworks for process parameters
Establish relationships between manufacturing conditions and conductor performance
Implement real-time process control strategies using sensor data and machine learning
Research Objectives
Design and validate forming processes for copper conductors
Develop finite element models to simulate the forming process
Investigate material behaviour and microstructural evolution during forming and its effect on the functional performance
Create adaptive optimization algorithms for process parameters
Implement data-driven approaches for process control and quality assurance
Establish design guidelines for scalable manufacturing
Methodology
The research will employ a comprehensive approach combining:
Experimental work on forming processes and material characterization
Advanced finite element modelling using commercial and custom software
Data acquisition and processing from manufacturing trials
Machine learning techniques for process optimization
Industrial validation of developed technologies
Required Qualifications
Higher 2.1 or a 1st MEng degree in Mechanical Engineering, Materials Science and Engineering, Metallurgy, Civil and Structural Engineering, or related field
Adequate knowledge of metal forming processes and manufacturing processes
Experience with finite element modelling software and mechanical testing is preferred (e.g., Abaqus)
Programming skills (Python, MATLAB, or similar)
Knowledge of materials science and metallurgy
Desired Skills
Experience with data analysis and machine learning
Knowledge of electric motor design principles
Familiarity with instrumentation and sensor systems
Background in process control and optimization
Good communication and technical writing skills
Industrial Collaboration
The project will be conducted in collaboration with leading manufacturers of electric motors and aerospace OEMs, providing exposure to industrial applications and potential career opportunities.
Funding Notes
Full funding for 3.5 years, including:
Tax-free stipend of standard EPSRC rate for home students
research and training grant
Coverage of tuition fees for Home applicants
If you are interested in this PhD please get in touch with Professor Hassan Ghadbeigi h.ghadbeigi@sheffield.ac.uk