Manufacturing
Modelling and simulation
Shaping the future of manufacturing with digital innovation
Based in the School of Mechanical Engineering, we advance manufacturing research through the integration of modelling, simulation, and digital technologies. By leveraging tools such as digital twins, artificial intelligence (AI), machine learning (ML), and computational simulations, our rationale is to empower researchers and industry partners to revolutionise manufacturing processes and systems for greater efficiency, precision, and sustainability.
Our research focuses
- Advanced computational modelling: computational simulations are at the core of our manufacturing research, enabling virtual testing and optimisation of processes across a range of applications such as “fluid and thermal systems” using computational fluid dynamics (CFD); “structural and materials simulations” using discrete element methods (DEM) and finite element analysis (FEA); “multiphysics modelling” for comprehensive system studies.
- AI and ML: To explore innovative approaches to solving complex problems, our research explores “data-driven solutions” for smart production planning, defect detection/correction, and generative design; “optimisation algorithms” for efficient resource management.
- Digital twins: enabling real-time virtual replicas of physical manufacturing systems, we pave the way for more intelligent and more connected production environments. By integrating advanced simulation tools, data analytics, and emerging technologies like IoT, AI, and ML, we bridge the gap between the physical and digital realms to create innovative, efficient, and sustainable manufacturing systems.