Digital Twin modelling and Robust MPC for improving the energy efficiency in manufacturing processes
- Digital For Society, Smart Manufacturing
- PhD Project
Project Summary
This project aims to develop a modelling framework for a high-fidelity digital twin of machining processes that can be continuously updated using real-time data. This digital twin model will be built upon the application of machine learning and systems and control theory to enable dynamic adaptation to process variations. The project will also design a predictive control strategy that leverages this evolving model to optimise machining operations and minimise energy consumption.
Research Questions
- How can machine learning and control theory be combined to enhance the digital twin’s adaptive capability?
- How can a predictive control strategy informed by the evolving digital twin model be designed to minimise energy consumption in machining operations?
Our Role
Collaborators
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- Supervisors:
Funding Acknowledgements
This research work has been supported by Science Foundation Ireland (SFI) Confirm Centre for Smart Manufacturing (CONFIRM), under Grant Number SFI/16/RC/3918.
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