SentientSystem was used in an optimisation project with the Electricity Power Research Institute (EPRI) in USA. The goal was to achieve cost savings related to soot blowing practices in a power plant.

EPRI wanted to see how an intelligent system could reduce costs by utilising existing data to provide insight and mathematically optimise the process.

The scope of the project involved research and implementation for applying Sentient System to incorporate multiple processes within a system and achieve optimisation – with no added instrumentation.

Our existing technology made it highly cost-effective to model the process, implement optimisation calculations, and automatically control the complex interactions. A web tool allowed operators to check on the performance improvements being achieved.

The project achieved payback of 12 months, through measured increase in unit efficiency. A 40% increase in mean time between failure for high-wear assets in the system was also achieved, significantly increasing the reliability of the plant and further increasing the value from the system.

    • 950MW coal-fired plant
    • Reduced reheat sprays by 33%
    • Reduced sootblow rate by 50%
    • Increased mean time-to-failure by 40%
    • Saved $700,000 per year through performance improvement and improved component life


Optimisation projects on complex assets


Research in greenhouse gas monitoring

In 2011, SentientSystem was utilised as the core technology in an engineering thesis on Performance Engineering. The research involved relating key power plant process metrics to greenhouse gas emissions .

As a project linking university research with industry, SentientSystem provided the integration of power plant sub-sytems, as well as the calculation engine for carbon emissions.

On the user interface side, SentientSystem also provides a significant library of web tools that was used to create dashboards and visualisations related to greenhouse gas emissions.

The ability to have verified measures of carbon emissions in both a monitored and virtualised system gives plant operators the insight and confidence to improve their financial and environmental bottom line in accordance with government regulations.

  • Industry CEED project for final-year engineering thesis
  • Winner of ‘Best Software Engineering Project’ from UQ
  • Presented at the IEEE, Power and Engineering Society Conference in San Diego, 2012

Energy efficiency is a problem that has not been tackled in mining, despite other industries doing so. Mathematical and integration complexity has put a high gap between current understanding and realisable optimisation of mines.

Employee Sam Patterson is a PhD candidate looking to address this, with SentientSystem acting as core technology by providing a modelling framework and calculation engine. Further, SentientSystem is extensible and flexible; capable of working with the real-world simplifications necessary to create a holistic operations model.

Our future doctor is extending this by comprehensively applying the technology to mining subsystems, and using novel computational techniques to make the optimisation solutions possible in real-time.

  • Industry-sponsored project at Queensland University of of Technology
  • Demonstrated commercial applications


Research in mining energy efficiency


Power asset performance insight

SentientSystem monitors power plants in Australia, Asia, North America and Europe.
Using existing data collection infrastructure, we apply comprehensive plant thermodynamics to enhance your understanding of asset conditions.

Multiple solutions are available to enhance your strategic knowledge of power generation assets, including performance and financial calculations, early warning of deviations, data visualisation and performance dashboards.

  • Managing over $15 billion of assets worldwide
  • The technology used by technology providers