University of Sheffield
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This exciting research project tackles a major challenge in precision manufacturing: residual stress related machining distortion. Distortion is especially problematic in high-value aerospace components, such as thin-walled structures, where even minor geometric deviations can lead to costly rework, wasted materials, difficulties during assembly, and extended production times. For example, it was estimated that distortion in thin-walled aerospace components resulted in over $290 million in losses across four different aircraft programmes in a single company.
Machining distortion is influenced by several factors, such as the workpiece material bulk residual stresses (influenced by heat treatment, mechanical processing, material properties, and microstructure), the stresses induced during machining, the component fixturing method, and the sequence of machining operations. All of these factors must be understood and considered in the simulation to accurately predict and mitigate machining distortion.
What You Will Do
You’ll develop a smart real-time simulation framework to predict and control machining distortion in aerospace components. Using hybrid techniques that combine numerical modeling techniques, like the finite element method, with advanced analytical models, your work will pave the way for smarter, more sustainable manufacturing practices.
Throughout this project you will work closely with both the AMRC Digital Machining team and the school of Mechanical, Aerospace and Civil Engineering at the University of Sheffield. You will also conduct experimental machining tests at the AMRC using our state-of-the-art machine tools and facilities.
Key Research Objectives
- Build upon existing analytical models to consider large deformations and combine them with numerical techniques to better account for real-world complexities.
- Extend the capabilities of analytical and hybrid models to simulate distortions in complex aerospace components.
- Develop and integrate a real-time simulation approach that uses live data to enable in-process adjustments to the machining process to prevent distortions before they happen.
Why It Matters
Your research will support the current trends in aerospace manufacturing by enabling the use of novel lightweight materials and automated precision assembly techniques. Through leveraging predictive models for real-time distortion control, you’ll help leading aerospace companies like GKN Aerospace, Boeing, and Airbus improve fuel efficiency, reduce emissions, reduce manufacturing costs, and maintain the highest quality for critical components. Making a tangible impact on the future of the aerospace industry.
Benefits
- Earn While You Learn: Get a fully funded four-year postgraduate research degree (EngD or PhD) with an annual tax-free stipend of £28,000 (that’s equivalent to a £34,000 salary!). We’ve got your back so you can focus on your research.
- Serious Funding: You’ll have access to a £35,000 research training support grant over four years. Whether it’s for experimental work, conference travel, or the latest computing gear, we’ll make sure you have the resources to succeed.
- Launch Your Career: Our graduates have landed senior roles in top industries, thanks to the hands-on experience and industry connections you’ll build here.
- World-Class Facilities: You’ll be working at the cutting edge, alongside experts in machining, assembly, and digital engineering. The tools and knowledge you’ll gain are second to none.
- Tailored Training: Benefit from both group-based and personalised training activities. We’ll help you craft an individual training plan that aligns with your career goals.
- Live in Sheffield: Enjoy life in one of the UK’s friendliest cities. With a vibrant social scene and supportive community, Sheffield is the perfect place to live and learn.
- Go Pro: We’ll support you in gaining Chartered Engineer (CEng) status, ensuring you’re recognised for your professional expertise.
Requirements
A first-class or strong 2:1 degree in a relevant science or engineering subject such as Mechanical Engineering, Aerospace Engineering, Materials Science, Physics or Computer Science
If English isn’t your first language, you’ll need an overall IELTS score of 6.5 with at least 6.0 in each section
Learn More
MADE4Manufacturing CDT: www.sheffield.ac.uk/made4manufacturing
Interested?
Contact Dr Sabino Ayvar-Soberatnis ([email protected]) for more information or go to our website to apply: https://www.sheffield.ac.uk/made4manufacturing/how-apply
When applying, please make sure you select ‘Doctoral Training Course’ as the qualification you are applying for. You should then select ‘MADE4 Manufacturing CDT’ for the specific doctoral training course, choosing either EngD or PhD as indicated in the project title.
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