Machine learning and Prognostics 

This project brings together the power of machine learning and predictive data analytics to improve prediction of equipment failures and optimise predictive maintenance strategies.

Social Internet of Things for Industrial Systems

This project aims to deliver a step change in efficiency and performance to the world of manufacturing by bringing together the advances in three domains – the Internet of Things, Social Networking and Engineering Asset Management.

Condition-based Maintenance Optimisation

This project aims to understand how assets affect system performance by modelling complex behaviors of such assets, e.g., interactive deterioration between components in an asset, fault propagation between assets in a system.

Maintenance of Asset Portfolios

This project focusses on optimising maintenance plans for asset fleets and portfolios under budget and resource constraints.

Criticality-based Maintenance

This research addresses an increasing need in the industry to prioritize maintenance activities  and investments based on the criticality and associated risk of assets.