This project is one of a number that are in competition for funding from the University of Bath URSA competition , for entry in September 2025.

Early application is encouraged, as excellent candidates may receive an early offer of a funded place before the end of the year. To be eligible for early consideration, you must apply before 24 November 2024.

Remanufacturing is a critical enabler of sustainability by promoting the reuse of products and minimizing raw material waste, resource extraction, and CO2emissions. It plays a vital role in ensuring that materials and products remain valuable over multiple lifecycles, reducing the environmental impact associated with new production, and finally contributing to a greener, more resilient, and resource-efficient economy. As industries worldwide adopt circular principles, remanufacturing will gain prominence as an essential process for meeting environmental goals and addressing resource challenges.

Remanufacturing aims to restore products to their original specifications, functionality, and performance. It can be applied to a variety of products, including electronic gadgets, vehicle engines, and medical equipment, especially suitable for some high-value, critical components in a product. Depending on the specific products/demonstrators, remanufacturing process chain could involve a series of steps or sub-processes that returns used products to a like-new or even-better condition. There are several potential sub-processes in the remanufacturing that AI & robotics can be featured to empower the next-generation remanufacturing process, e.g., Automated Disassembly, Inspection and Condition Assessment, Sorting and Classification of Components, Additive Manufacturing and Repair, Remanufacturing Process Optimization (Digital Twins), End-to-End Data Integration and Supply Chain Optimization, Autonomous Quality Control, Human-Robot Collaboration (Cobots), and Predictive Maintenance for Equipment. In this PhD project, we wiil focus on 2 or 3 sub-processes that can be empowered by AI and robots:

(1) Automated Disassembly. Disassembly is a critical stage in remanufacturing, involving complex tasks of reverse engineering. Traditionally, it is labor-intensive, time-consuming, and error-prone. Robotic systems powered by AI vision, reinforcement learning, and automated planning algorithms canautomatically disassemble products. Using real-time feedback, these systems can adapt to uncertainties, identify optimal disassembly sequences, and handlea variety of product types without predefined instructions. This leads to higher efficiency, reduced labor costs, and a lower risk of human error, makingremanufacturing scalable.

(2)Additive Manufacturing and Repair. In many remanufacturing cases, components may require repairs, such as replacing missing sections or restoringdamaged parts. Combining AI with additive manufacturing (AM), allows for highly customized and precise repair solutions. AI systems can optimize designsand manufacturing processes based on real-time data from the defective part, ensuring minimal material usage and high-strength repairs. AI-driven additivemanufacturing enhances the flexibility and precision of remanufacturing operations, reducing material wastage and enabling personalized repairs at scale.

(3)Human-Robot Collaboration (Cobots). Certain aspects of the remanufacturing process still require human intervention, particularly in handling complexand unpredictable tasks. Collaborative robots (cobots) can work alongside human operators to assist in tasks like disassembly, sorting, and componentreassembly. AI enables these robots to learn from human inputs, making them more flexible and able to handle a wider range of tasks.

Candidate requirements:

Applicants must have, or be about to obtain, a UK Honours degree 1 ^st or 2.1, or international equivalent.

A Masters degree would be advantageous.

Non-UK applicants, who are not currently studying in the UK, must meet the programme’s English language requirement before the application deadline – no exceptions will be considered.

Enquiries:

Informal enquiries are encouraged! Direct these to Dr Quanren Zeng - [email protected]

Application Instructions

Please follow the below instructions carefully.

You must make a formal application via the University of Bath’s online application form for a PhD in Mechanical Engineering

Please note that you can apply for a maximum of two PhD projects on this programme.

In the ‘Funding Your Studies’ section, you must select ‘University of Bath URSA’ from one of the drop-down menus.

In the ‘Your PhD project’ section, you must quote the project title in the PhD project title field, and you must quote the lead supervisor’s name in the field ‘Name of intended supervisor at University of Bath.’

If you are applying for two projects, you must quote the project title for your second choice project in the field ‘Project 2 Title’ and the lead supervisor’s name in ‘Name of intended supervisor for 2 ^nd choice project at University of Bath.

You must ensure that you follow the above steps correctly. Failure to complete these steps will cause errors in the automated processing of your application and may mean that you are not considered for a particular project.

Equality, Diversity and Inclusion

We value a diverse research environment and strive to be an inclusive university, where difference is celebrated and respected. We 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.

The Disability Service ensures that individuals with disabilities are provided the support that they need. If you state if your application that you have a disability, the Disability Service will contact you as part of this process to discuss your needs.

Keywords

Remanufacturing, sustainability, circular economy, AI-driven, Robotics, cobot, additive manufacturing