Engineering System Health

Engineering Asset Health


Remote engineering involves asset intensive industries such as energy, mining, infrastructure and transportation. Projects for these industries often include a myriad of assets diversified by function, geographic location and environmental and cultural context. Integrated system models and asset plans are now vital to unlock a project’s potential and provide insight for global business decision-making.  

Our researchers aim to bring significant change in the field of asset health management with improved sensing diagnostics and prognostics. We identify and minimise the gaps between research frontiers and practical application to improve predictive asset management, operation fault detection and a project’s overall lifecycle performance. 


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Problems that we solve

How do you assess the current health of your engineering assets? What is their likelihood of failure? Will assets survive to their predicted end-of-life? What is your confidence in your prediction and what are the implications if you are wrong?

Our research aims at improving prediction of asset health. We are active in all phases of the prediction process from sensor development to evaluation of statistical and machine learning prediction model performance.

We define engineering assets broadly with interests ranging from mooring lines and heavy mobile equipment to 3D printed parts and sensors for mine lake water quality.