Smart Manufacturing and Digital Twin Modelling for Remanufacturing Systems (PhD Funded)

This PhD at University of Exeter focuses on developing smart manufacturing and digital twin modelling frameworks for remanufacturing systems. Remanufacturing is a key pillar of circular economy strategies, enabling recovery and reuse of end-of-life products. However, the product recovery and material separation stages are highly uncertain, making optimisation and decision-making challenging. The project aims to design and implement advanced simulation and digital twin models to improve operational efficiency, resource recovery, and sustainability in remanufacturing systems. The research will support data-driven decision-making under uncertainty. Working with the Exeter Digital Enterprise Systems (ExDES) group, the student will: Develop digital twin frameworks for remanufacturing systems Build simulation models using tools such as AnyLogic, Simio, Python, or MATLAB Evaluate system performance and sustainability impact Improve optimisation of recovery and separation processes The project has strong applications in Industry 4.0, circular economy systems, and intelligent manufacturing optimisation.

Applicants should have:
First-class or strong upper second-class degree in Engineering, Manufacturing Engineering, Industrial Engineering, Systems Engineering, Operations Management, Computer Science, or related fields
Interest in manufacturing systems, simulation, and operations research
Knowledge of or interest in:
Digital twins
Discrete-event simulation
Agent-based modelling
Optimisation or decision support systems
Desirable:
Master’s degree in a related field
Experience with simulation tools or programming (Python, MATLAB, AnyLogic, etc.)

Apply via:
https://www.exeter.ac.uk/study/funding/award/?id=5831
Required documents typically include:
CV
Academic transcripts
Supporting statement (if required)
References