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Leveraging craft knowledge and AI towards waste-free, digital manufacturing processes

   Department of Mechanical Engineering

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  Dr Evripides Loukaides  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project

The department of Mechanical Engineering at the University of Bath is inviting applications for the following fully funded PhD project, expected to commence as soon as possible and before September 2023.

This studentship is affiliated with the Centre for People-Led Digitalisation and its many industrial partners. 


Several craft industries oppose automation and digitalization on the basis that they lack authenticity and on the implicit understanding that handmade objects are inherently better. At the same time, the tacit knowledge and flexibility of a skilled craft worker is a diminishing commodity that needs to be captured and transferred to modern manufacturing processes. The process of reconciling these two views and ensuring the posterity of valuable knowledge, while promoting sustainable industrial growth, has to consider both human and technical factors. This project will pursue this objective by focusing on the requirements and challenges of automating flexible manufacturing processes, with a focus on metalworking.

The project will build bridges with craft workers and capture their digital hesitancy. At the same time, it will suggest ways for human knowledge and influence to be maintained in a useful way during automation development for processes that will serve as case studies. It will translate craft knowledge to quantifiable engineering principles or alternatively identify communication gaps. The lessons from these case studies will then be generalised as guidelines for wider adoption in several industries. In particular, the automation of flexible, craft processes can deliver low waste processes with minimal scrapping of materials and without dedicated tooling, therefore enhancing sustainability goals.

The project requires contributions from several domains and the diverse expertise already available to the Centre for People-Led Digitalisation (PLD). To learn more about PLD please see

Candidate Requirements

Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree (or the equivalent) in mechanical or production engineering, material science, applied mathematics or similar disciplines and an interest in manufacturing automation and its impact on workers and organisations. A master’s level qualification would also be advantageous.

Non-UK applicants must meet our English language entry requirement.

Enquiries and Applications

Informal enquiries are welcomed and should be directed to Dr Evripides Loukaides - [Email Address Removed]

Formal applications should be made via the University of Bath’s online application form for a PhD in Mechanical Engineering

More information about applying for a PhD at Bath may be found on our website.

Funding Eligibility

To be eligible for funding, you must qualify as a Home student. The eligibility criteria for Home fee status are detailed and too complex to be summarised here in full; however, as a general guide, the following applicants will normally qualify subject to meeting residency requirements: UK nationals (living in the UK or EEA/Switzerland), Irish nationals (living in the UK or EEA/Switzerland), those with Indefinite Leave to Remain and EU nationals with pre-settled or settled status in the UK under the EU Settlement Scheme). This is not intended to be an exhaustive list. Additional information may be found on our fee status guidance webpage, on the GOV.UK website and on the UKCISA website.

Equality, Diversity and Inclusion

We value a diverse research environment and aim to be an inclusive university, where difference is celebrated and respected. We welcome and encourage applications from under-represented groups.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.


Flexible Manufacturing, Metal Forming, Automation, Machine Learning, Craft Processes, Applied Mathematics, Artificial Intelligence, Human Computer Interaction, Machine Learning, Manufacturing Engineering, Mechanical Engineering, Metallurgy, Robotics, Solid Mechanics, Systems Engineering, Computational Mathematics, Data Analysis, Engineering Mathematics, Stochastic Processes

Funding Notes

Candidates applying for this project will be considered for a 3-year University of Bath Studentship which will cover tuition fees at the ‘Home’ rate, a training support fee of £1,000 per annum and a tax-free maintenance stipend (value TBC). In order to be eligible for funding, applicants must qualify as a ‘Home’ student - see Funding Eligibility section above.


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