Smart Manufacturing and Digital Twin Modelling for Remanufacturing Systems (PhD Funded) University of Exeter in United Kingdom

This funded PhD position at the University of Exeter focuses on advancing smart manufacturing and digital twin modelling for remanufacturing systems. Remanufacturing is a cornerstone of sustainable and circular production, enabling the recovery of value from end-of-use products and components. The project addresses the critical stage of product recovery and material separation, which significantly impacts system performance, cost efficiency, and environmental outcomes. Conventional approaches often struggle with uncertainties in this stage, making planning and optimisation challenging.

As part of the Exeter Digital Enterprise Systems (ExDES) research group within the College of Engineering, Mathematics and Physical Sciences, the successful candidate will develop advanced modelling and simulation frameworks to support decision-making in smart remanufacturing systems. Key objectives include creating a conceptual modelling and digital twin framework to enhance decision-making under uncertainty, designing and implementing simulation models using tools such as AnyLogic, Simio, Siemens Plant Sim, Python, MATLAB, or other relevant platforms, and evaluating the proposed framework to assess its impact on operational efficiency and sustainability.

The research is highly interdisciplinary, drawing on manufacturing engineering, operational research, and data analysis. Candidates will gain expertise in discrete-event simulation, agent-based modelling, systems modelling, digital twins, optimisation, and decision-support systems. The project aims to deliver practical solutions for improving resource efficiency and sustainability in remanufacturing contexts.

Applicants should have a strong academic background in Engineering, Industrial Engineering, Manufacturing Engineering, Systems Engineering, Operations Management, Computer Science, or a related field. A first-class or strong upper second-class undergraduate degree (or international equivalent) is required, and a master's degree in a relevant area is desirable but not essential. Prior experience in simulation modelling, digital twins, and optimisation is highly valued.

The studentship offers full coverage of UK and International tuition fees and an annual tax-free stipend of at least £21,805. The application deadline is April 14, 2026. For further information and to apply, visit the University of Exeter funding page or the FindAPhD project listing. This opportunity is ideal for motivated candidates seeking to contribute to sustainable manufacturing and digital innovation in remanufacturing systems.