About the System Health Lab

Learn more about the System Health Lab below

The System Health Laboratory provides a dynamic environment for engineering, computing and mathematics students to work on challenging multi-disciplinary projects aimed at improving the maintenance of assets.

Our overarching aim is to assist young engineers to gain competence and confidence that will enable them to transition smoothly into the workforce, research roles or start their own companies.

We have a strong commitment to open source hardware and software. Where possible we leverage open source analysis tools and intend to openly share data and models we create to encourage interaction. Our hardware platforms are flexible enough to incorporate the latest in low-cost interfaces, removing barriers to entry for researchers interested in data collection. Many of the projects involve rapid prototyping of sensing or test systems, data analysis and visualization.

The System Health Lab is also a meeting place, leveraging the industry links of the Lab’s leadership team, to support current students meeting practicing engineers and engaging in industry workshops and conferences. The three main research aims are described in the section below.

Research focus areas

Assets fail. Sometimes these failures are spectacular and unexpected. Safety can be compromised and production or service impacted. These failures capture the attention of senior management and sometimes the media. More often failures have low consequences but occur frequently. These failures upset the smooth running of the operation and result in unplanned work and additional expenses.

The specific aims of our group are to:

Aim 1: Develop processes to efficiently predict asset failures so that maintenance work can be planned and disruption avoided.

Currently asset failure prediction (and to a lesser extent diagnosis) relies on a high level of human expertise both to set up and to use.

Aim 2: Develop an efficient, effective and adaptive process for selecting sensors, feature vectors, diagnostics and prediction algorithms for application to industry assets.

The work that maintenance technicians do on assets can either deliver availability or, if done incorrectly, destroy value. New technologies have the potential to change the way we support maintenance technicians to do their work.

Aim 3: Develop and deploy tools to assist maintenance technicians with decision making.


Our Supporters

The System Health Lab would not be possible without the support below

University of Western Australia