Maintenance Engineering

Maintenance Engineering research at Charles Darwin University (CDU) is supported by Clough, and the North Australian Centre for Oil and Gas (NACOG) Consortium,

Clough works with some of the world's largest energy and resource companies to engineer, construct, commission and maintain a range of infrastructure for energy, chemical, mining and mineral projects, and has a broad range of experience in maintenance engineering.

The recently-launched Clough-CDU Maintenance Engineering Collaboration (CCMEC),,  brings the specialist research capabilities of CDU together with Clough’s proven maintenance engineering expertise to support the oil and gas and other industries’ maintenance engineering and asset management requirements.
The North Australian Centre for Oil and Gas (NACOG) is a hub located at CDU for training and education programmes (both on campus and externally through distance learning), together with research capabilities targeted at the specific needs of oil and gas operations and developments in the region.

Oil and gas companies are facing many challenges in terms of maintenance. They are facing increasing cost pressures due to the current oil price level and the need to reduce their CAPEX and OPEX. They have to reduce their unscheduled maintenance, optimise their production and improve their maintenance planning. It is no more viable to flood men in boots for failures or maintenance problems. They have to bring intelligence into maintenance.

The Maintenance Engineering research at CDU focuses on real-time prediction of failures, availability and plant performance via Prognostics Health Management (PHM). The prognostics research is complemented by research in Maintenance Optimisation, Asset Integrity, Through-life Cost Estimation, Microbiologically-Influenced Corrosion (MIC), Safety and Specialist Maintenance Advice.
We are currently working with both with the oil and gas sector and the mining sector in our Maintenance Research.

Predictive Maintenance via Prognostics Health Management

Prognostics Health Management enables the prediction of failures and planning maintenance well in advance of the failures by using the data available from already-installed sensors and new sensors on assets. The CDU team focuses on intelligently extracting useful information from related failures and then using them to predict maintenance activities of the assets. We also use artificial intelligence and cloud computing to automate the predictive maintenance activities in real-time.  

Research Coordinator: A/Prof Sureshkumar


PhD Topics