Simulation of laser based processing of polycrystalline composites combining analytical and machine learning models PhD

Mechanical, Electrical and Manufacturing Engineering
Entry requirements:
3 years
6 years
Reference number:
Start date:
01 October 2018
UK/EU fees:
International fees:
Application deadline:
09 March 2018



in the UK for research quality

REF 2014


in the UK for Mechanical Engineering

The Complete University Guide 2018


of 2 Queen's Anniversary Prizes


Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. 

Project detail

Laser milling has recently gained interest in industry for finishing ultra-hard cutting tools, especially in the automotive field. In laser milling, different combinations of materials properties and machining parameters lead to various topographical profiles and the actual removed volume needs to be estimated accurately to achieve accurate simulations. For polycrystalline composites, due to the complex microstructure of grains/binder, the laser milling optimisation process is still based on trial and error experiments, resulting in a not efficient and limited use in industry.

Researchers have been investigating various way of predicting the laser milling process for monocrystalline materials. However, for polycrystalline composites analytical models representing accurately the physical behaviour of thermal ablation process remain to be developed. This project aims at developing a 3D geometrical simulation tool for laser ablation of polycrystalline ultra-hard material.

The successful candidate is expected to develop a novel model which combines machine learning models with more conventional thermal analytical models, populate the necessary databases from past and new experiments and to characterise the milled surfaces with various techniques.

This research will benefit from direct involvement of industrial partners including ultra-hard material and cutting tool manufacturers, helping the candidate to build a strong understanding of the machining involved in automotive and aerospace industries.


Primary supervisor: Dr Manuela Pacella

Secondary supervisor: Prof. Vadim Silberschmidt

Find out more

For further project details email Dr Manuela Pacella or register your interest and ask us a question.

To find out more about the School of Mechanical, Electrical and Manufacturing Engineering, please visit our website.

Entry requirements

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Manufacturing/Materials Engineering or Computer Science. 

A relevant Master’s degree and/or experience in one or more of the following will be an advantage: laser processing, artificial intelligence and modelling. 

All students must also meet the minimum English Language requirements.

Fees and 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. Special arrangements are made for payments by part-time students.

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.

How to apply

All applications should be made online. Under programme name select Mechanical and Manufacturing Engineering. Please quote reference number: MPUF2018