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Artificial intelligence in additive manufacturing: use of deep-learning in dimensional accuracy of stereolithography 3D printing

   Wolfson School of Mechanical, Electrical and Manufacturing Engineering

  Dr E Sabet, Dr G Cosma  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

This project offers a chance to work on a truly disruptive and innovative research project in high-tech and high-value manufacturing, with a very high potential impact in aerospace and energy sectors. This project runs under a consortium between Loughborough University and a British innovative industrial partner, Photocentric Ltd.

This project positions in the between two very innovative and got topic research area of machine learning and additive manufacturing, and aims for developing deep-learning algorithms to predict and thus improve dimensional accuracy and stability of 3D printed products.

This research intends to focus on a novel LCD-based stereolithography 3D printing with high print resolution needed for highly accurate applications. However, to minimise deformation during print and post-print operations, a deep-learning model will be developed and trained to predict shrinkage, deformations, and shrinkages to enable the designers to better design the parts and 3D print processes.

Find out more

The industrial partner of this project, Photocentric Ltd, is a patent holder in visible light curing technologies, specialising in photopolymerisation and inventors of LCD based 3D printing. Photocentric is an award-winning specialist 3D resin and LCD printer manufacturer based in Cambridgeshire, UK and Arizona, USA.


Primary supervisor: Dr Ehsan Sabet

Secondary supervisor: Dr Georgina Cosma

Entry requirements for United Kingdom

Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent international qualification) in computer science, mathematics, polymer science, mechanical engineering, manufacturing engineering, or other relevant backgrounds with high credentials. Applications must have significant knowledge of AI, programming and modelling, but knowledge of additive manufacturing is only desirable, as the students will be fully trained on additive manufacturing techniques needed for this project, as part of their first year of their PhDs. As part of the application process, candidates are required to write a research proposal.

This project has some industrial clients who may be able to contribute to the cost of experiments/tests, but applicants must be able to fund their study (tuition fee and living expenses).

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.

Find out more about research degree funding

Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.

How to apply

All applications should be made online. Under school/department name, select 'Mechanical and Manufacturing Engineering'. Please quote reference UF-ES-2022-2

Apply now

Funding Notes

UK fee - £4,596 full-time degree per annum
International fee - £25,100 full-time degree per annum
This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.
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