Emmanuel Lwele
Emmanuel Lwele
Email: el1245@hallam.shu.ac.uk
Research Centre: NCEFE
Research Group: Digital connectivity and technology
PhD Thesis Title: AI-based surrogate models of digital twins for Industrial Processes
Director of Studies: Prof Alex Shenfield
Supervisors: Prof Alex Shenfield, Carlos Da Silva
SUMMARY
I am a PhD student in Robotics and Machine Learning and currently researching digital twins and surrogate modelling in the manufacturing industry
RESEARCH
My research focuses on developing AI-based surrogate models for digital twins in industrial processes.
Digital twins are virtual replicas of physical systems, providing real-time data and predictive insights. However, their computational demands can be high. Surrogate models, powered by AI, offer a solution by approximating the behavior of complex systems with reduced computational effort. These models leverage machine learning algorithms to predict system performance, optimize processes, and enhance decision-making.
By integrating AI with digital twins, we aim to improve the efficiency, accuracy, and scalability of simulations in industrial settings, leading to enhanced operational efficiency, reduced costs, and improved system reliability. This research has the potential to revolutionize how industries manage and optimize their processes in real-time.
